Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 436 appraisals
JMIR formative research
Teaching Health Informatics in a Skills-First Era: A Curriculum Mapping Approach Aligned With Workforce Demand
Academic programs in health informatics have been urged to align curricula with evolving workforce needs to better prepare graduates for practice. Such alignment supports workforce readiness, addresses talent shortages, and reduces onboarding burdens for employers. Although employers increasingly seek graduates who can demonstrate applied skills and competencies beyond textbook knowledge, academic programs continue to face challenges in translating workforce demand into curricular design. This Viewpoint is directed at health informatics program faculty and administrators and presents the author's perspective on a skills-first curriculum mapping approach aligned with current industry needs. The author argues that connecting program-level outcomes, course objectives, and learning activities to industry-recognized competencies strengthens workforce readiness while maintaining academic rigor. Drawing on the literature on competency-based education, workforce development, and health informatics training, this paper argues for intentional curriculum design that integrates transferable skills, stackable credentials, and stakeholder engagement. The key messages are as follows: (1) workforce demand should anchor curriculum design in health informatics programs, (2) curriculum mapping is a practical mechanism for operationalizing skills-first alignment, and (3) credential integration and continuous congruency evaluation support long-term program sustainability. This approach positions health informatics education to remain responsive, scalable, and aligned with the rapidly evolving professional landscape.
31 July 2026
Read appraisal →Proceedings of the National Academy of Sciences of the United States of America
Race-conscious admissions algorithms and the law.
In recent years, colleges and universities have begun to use machine learning (ML) systems to inform admissions decisions. Meanwhile, in the 2023 case Students for Fair Admissions, Inc. v. President and Fellows of Harvard College, the Supreme Court held that colleges and universities may not make admissions decisions "on the basis of race." These parallel developments-the rise of ML in admissions and the fall of race-based affirmative action-will force educational institutions, and ultimately courts, to confront the difficult question of what it means for ML systems to differentiate "on the basis of race." We begin by mapping the Students for Fair Admissions decision onto different uses of race in predictive AI. We distinguish between "first-order" and "second-order" race consciousness at both the training and predictive phases of machine learning, and we argue that each category of race consciousness raises distinct legal and normative issues. We go on to show that the Students for Fair Admissions decision potentially permits-and even endorses-certain forms of race consciousness. Our analysis is grounded in the observation that the process of developing ML-based systems enables policymakers to calibrate decision making algorithms much more precisely and explicitly in response to specific criticisms of race-conscious affirmative action.
28 July 2026
Read appraisal →Journal of medical Internet research
Digital Transformation in Health Care: Are We on the Right Track?
Health care digital transformation is gaining increasing attention, despite the observed challenges in its implementation. The envisioned benefits, together with the growing need for better health care, are motivating academia, organizations, regulatory agencies, and governments to develop more effective digital health care solutions. Through extensive debates among the authors, this paper discusses how digital transformation is being conducted in the health care sector. Our discussion relies on concepts from sociotechnical systems theory, categorizing it into 3 social (people, culture, and goals) and 3 technical (processes/procedures, infrastructure, and technology) dimensions. Drawing on both the literature discussed in this paper and our combined academic and practical experience-each author contributing over a decade of work in health care digital transformation-we examined current digitalization efforts from a sociotechnical standpoint. Overall, we argue that both social and technical dimensions present elements that have either encouraged or discouraged the progress of health care digital transformation. The identification of current trends on such (on- and off-track) elements allowed the formulation of 12 propositions across each sociotechnical dimension for future testing and validation. This approach can help establish better government policies, foster private initiatives, and shift regulatory guidelines to support a successful digital transformation in health systems. Finally, from a research perspective, we outline some opportunities for further interdisciplinary investigation in the field, promoting advances in the understanding of health care digital transformation.
22 July 2026
Read appraisal →PloS one
Self-positioning in space science communication: A corpus-assisted discourse study
This study incorporates text mining into critical discourse analysis to examine how government science agencies in China and the United States position themselves in space science communication on social media. Two specialized corpora have been built by collecting posts from government science agencies on Weibo from China and X (formerly Twitter) from the U.S. With the help of the text mining tool KH Coder, this study gives a corpus-assisted discourse analysis of the particular ways of positioning at different levels of discourse: (1) topics/themes, (2) addressing terms, and (3) those words that co-occur with self-addressing terms in a sentence. The findings reveal significant differences in their preferential ways of positioning. Chinese government science agencies present themselves as state-affiliated yet approachable institutions, blending achievements and operational efficiency with patriotism and collective pride. Their use of diverse addressing terms and co-occurrence patterns portrays them as experienced, supportive guides, balancing national identity with interpersonal closeness. In contrast, U.S. government science agencies emphasize professionalism, focusing on research, space exploration, mission execution, and audience engagement, with minimal reference to state affiliation. Their addressing terms are formal and standardized, with pride centred on mission success and discovery, highlighting expertise and scientific leadership. Their preferential ways of positioning are further explained in their respective contexts in order to present a proper understanding of these differences.
12 July 2026
Read appraisal →JMIR infodemiology
Self-Reported Tianeptine Experiences on Reddit: Natural Language Processing-Assisted Qualitative Study
This study, using natural language processing and manual thematic analysis of Reddit posts, revealed a rapid rise in discussions about tianeptine, with posts frequently reporting dependence, withdrawal, and coingestion with other unregulated substances, highlighting tianeptine as an emerging public health concern.
8 July 2026
Read appraisal →Journal of medical Internet research
Are Traditional Registries Becoming Obsolete in the Modern Digital Health Ecosystem?
Registries have long been a cornerstone of medical research and public health, providing systematically collected data on diseases, treatments, and health outcomes. However, in the era of digital health, we argue that the traditional model of stand-alone registries needs reconsideration, given the context of increasingly digitized and interoperable health data ecosystems. Unless registries evolve to embrace embedded, standards-based data services, operating across interoperable infrastructure, they will become obsolete while digitalization is reshaping how data can be collected, shared, and used. In this viewpoint, we recount how the present health data ecosystem came to be and what role registries have come to play therein. Following that, we show how recent regulatory initiatives such as the Trusted Exchange Framework and Common Agreement in the United States or the European Health Data Space Regulation signal a shift toward cross-network health information exchange, promoting patient-centric data integration within electronic health record systems. We further illustrate how electronic health records are consequently set to evolve into information hubs, acting as the primary gateway for individuals through which they may access and control their personal health data spread throughout increasingly connected health data ecosystems. This, in turn, might stimulate the creation of digital twins and continuous learning health systems in practice. Following this line of thought, we discuss the opportunities and challenges of interconnected health data ecosystems. Ultimately, we propose that next-generation registries need to be designed as dynamic, service-oriented software stacks for research, leveraging the common data infrastructures that are currently being established around the world. Given the points raised in this viewpoint, we invite health care professionals and researchers alike to equally rethink the role that registries should play within the globally emerging interconnected health data ecosystems and contribute their findings. References included in this viewpoint were identified through searches of PubMed and Google Scholar with various search terms and combinations thereof pertinent to the topics touched on, for example, "patient registry," "clinical registry," "digital twin," "healthcare," "clinical research," "virtual twin," "TEFCA," or "EHDS." Only papers in English were reviewed. The final reference list was generated on the basis of originality and relevance to the broad scope of topics covered in this viewpoint, aiming to present a balanced overview of topic-related findings and arguments.
5 July 2026
Read appraisal →JMIR formative research
Knowledge, Attitudes, and Practices Related to AI in Learning and Research Among Medical Students in Vietnam: Cross-Sectional Study
BACKGROUND: In recent years, artificial intelligence (AI) has ushered in a promising era in medicine, particularly in medical education. However, studies assessing the knowledge, attitudes, and practices related to AI among medical students in Vietnam remain limited. OBJECTIVE: This study aimed to evaluate AI knowledge, attitudes, and practices among Vietnamese medical students in learning and research, and to identify factors associated with their AI practices. METHODS: A cross-sectional study was conducted among medical students at Thai Binh University of Medicine and Pharmacy from November to December 2025. Data were collected using an online structured questionnaire covering demographic characteristics and AI knowledge, attitudes, and practices. The main outcome of interest was AI practices in learning and research. Descriptive statistics and multivariable linear regression were used to examine associated factors. Regression coefficients (β), 95% CIs, and P values are reported. RESULTS: A total of 1002 medical students (mean age 21.00, IQR 19.00-23.00 years; n=596, 59.5% female) were included. The median percentage of maximum possible (POMP) score of AI knowledge was 66.67 (IQR 33.33-83.33), with a high level of familiarity with common tools (n=798, 79.6%). AI attitudes were generally positive (median POMP score 70.00, IQR 53.33-76.67). AI-related practices were lower (median POMP score 50.00, IQR 46.88-71.88), with AI being used primarily for information retrieval and literature research support. In the multivariable analysis, knowledge POMP score (β=0.12, 95% CI 0.08-0.16) and attitudes POMP score (β=0.42, 95% CI 0.34-0.51) were significantly associated with AI practices POMP score (P<.001). Age, gender, major, grade point average classification, and having participated in an AI seminar or training were not associated with AI practices. CONCLUSIONS: Medical students showed favorable knowledge and positive attitudes, but their AI practices remained limited. Integrating AI into medical curricula, including fundamentals, applications, and ethical aspects, is essential to prepare future physicians for AI-driven health care.
5 July 2026
Read appraisal →Psychiatric services (Washington, D.C.)
Psychiatric Risk Associated With Large Language Model Chatbots: An Emerging Concern
Large language model chatbots such as ChatGPT have been adopted by millions of users, yet their psychiatric implications are poorly understood. Recent media reports describe 26 apparent instances of psychosis and two instances of depression and suicide in the context of heavy chatbot use, often marked by delusions seemingly reinforced by the model. Because chatbots simulate conversation but are statistical systems optimized for agreement, they may amplify distorted beliefs. Research is needed to determine whether these reports represent a genuine pattern of risk and to identify vulnerable populations. Clinicians should screen for chatbot use and discuss these systems with patients.
2 July 2026
Read appraisal →Current opinion in psychiatry
Opportunities and risks of large language models in digital interventions for substance use disorders
PURPOSE OF REVIEW: Large language models (LLMs) are increasingly integrated into digital mental health tools, yet their role in substance use disorder (SUD) interventions remains poorly understood. This review synthesizes emerging evidence on the opportunities and risks of applying LLMs across the digital SUD care continuum. RECENT FINDINGS: Studies report promising applications in early detection, personalized support, continuous monitoring, and relapse prevention. LLMs demonstrate capacity to extract substance-use signals from natural language, generate supportive and motivational responses, and interpret narrative data for patient-reported outcomes. However, risks are substantial. LLMs can produce inaccurate or hallucinated content, may reinforce stigma or demographic bias, and can generate misleading or potentially unsafe advice. Privacy concerns are amplified in SUD contexts, where sensitive data are often managed outside regulated healthcare systems. Existing regulatory frameworks such as the EU AI Act or U.S. device regulations, do not yet provide clear governance for anonymous, AI-supported SUD interventions. SUMMARY: LLMs have potential to expand scalable, low-threshold support for SUDs, but their safe deployment requires validation, bias mitigation, transparent data governance, and robust human oversight. Evidence remains preliminary, and clinical integration should proceed cautiously.
2 July 2026
Read appraisal →PloS one
Transformer-based advertisement image layout generation and object fidelity optimization
The layout of the image and the positional distribution of the objects directly affect the audience's visual focus and the effect of the message conveyed. By setting up a specific layout structure, the viewer's attention can be more focused on the product launched or the moral of the advertisement. Existing work related to position-controllable text-to-image generation has made great progress in generating results on simple images. However, when generating images of complex scenes, the quality is often poor. This can result in the model failing to accurately convey the message of the advertisement when used to generate advertisements. To address these limitations, we propose LAYOBJ-GAN, a novel two-stage framework for layout-controllable advertisement image synthesis. Unlike prior work, our method explicitly models background layouts jointly with object layouts during the text-to-layout generation stage, enabling comprehensive spatial planning of complex scenes. Technically, we introduce a Transformer-based sequence-to-sequence layout generator that learns long-range dependencies between textual descriptions and both background and object regions, which has not been explored in previous advertisement-oriented text-to-image frameworks. In the layout-to-image stage, we further propose a fine-grained text-layout interaction normalization module (TL-Norm) that enables object knowledge transfer from a pre-trained category-to-image model, allowing object appearance to be adaptively modulated by textual context and layout constraints. Extensive experiments on MS-COCO and a high-definition advertisement dataset (AsHQ-10K) demonstrate that LAYOBJ-GAN significantly outperforms seven state-of-the-art methods in image quality, layout controllability, and semantic object accuracy. These results confirm the effectiveness of explicitly modeling background layouts and transferring object-level generative knowledge for complex advertisement image synthesis.
27 June 2026
Read appraisal →Prehospital and disaster medicine
Non-Resuscitative Telecommunicator-Assisted First Aid: A Scoping Review
INTRODUCTION: The provision of instant telephone pre-arrival instructions (PAI) on first aid to laypeople by emergency services' telecommunicators for conditions beyond cardiac arrest, such as trauma or acute coronary syndrome, is practiced by emergency services around the world and is recognized by some prehospital systems as a standard of care. However, to the best of the authors' knowledge, no attempts have been made to date to systematically summarize the related research evidence. STUDY OBJECTIVE: The aim of this study was to systematically map and analyze published quantitative research on telecommunicator-assisted first aid (TAFA) for medical emergencies other than cardiac arrest. METHODS: Peer-reviewed journal papers reporting original quantitative data on experimental or real-world applications of TAFA were identified through PubMed, Scopus, and Google Scholar. Studies focusing solely on cardiac arrest management (cardiopulmonary resuscitation [CPR] or automated external defibrillation) were excluded. A scoping review of eligible papers was conducted in accordance with the PRISMA-ScR guidance. RESULTS: Twenty-two studies published from 2000 through 2024 met inclusion criteria. First authors represented nine high-income countries. The studies investigated hypothetical or actual application of TAFA for anaphylaxis, chest pain or myocardial infarction, stroke, trauma, bleeding, childbirth, foreign body airway obstruction, opioid overdose, and respiratory arrest; four studies did not specify the type of emergency. Eight studies (36.4%) analyzed real Emergency Medical Services (EMS) call data, another eight (36.4%) were simulation-based, five (22.7%) used surveys, and one (4.5%) represented a cost-effectiveness analysis. The studies described existing TAFA practices, evaluated expectations and perceptions of the service by the public, demonstrated the feasibility of experimental techniques, including video communication, and identified areas for future investigations and interventions. Along with some beneficial effects of TAFA, several studies have demonstrated downsides of the practice, including suboptimal dispatcher adherence to pre-arrival protocols. The relationships between the real-world application of TAFA and patient outcomes are unclear. CONCLUSION: According to the review of quantitative research, non-resuscitative TAFA remains an under-explored area of prehospital medicine. Considering the paucity and the inconclusiveness of available evidence, significantly more research is required to better understand its effects and practical implications. The evidence map generated by this scoping review may assist the professional community in advancing the development of non-resuscitative TAFA.
26 June 2026
Read appraisal →Journal of Korean medical science
Evaluating Large Language Models for Post-Publication Promotion: A Blinded Comparative Study of Social Media Posts in Public Health
BACKGROUND: Social media platforms such as X (formerly Twitter) are increasingly used by journals, authors, and institutions to promote newly published research. Well-designed posts can enhance visibility, accelerate knowledge translation, and increase altmetric attention. However, creating accurate and policy-compliant content is time-intensive. Large language models (LLMs) offer a potential solution, yet systematic evaluations of their performance in post-publication promotion remain limited. METHODS: We conducted a blinded, crossed, offline evaluation of four LLMs: GPT-5 (OpenAI), Gemini 2.5 Pro (Google DeepMind), Grok-3 (xAI), and Perplexity Pro (Perplexity AI), tasked with generating X-style posts (≤ 260 characters) for 36 open access articles from The Lancet Public Health, The Lancet Planetary Health, and Annual Review of Public Health. Posts were generated using a standardized system and user prompt. A single blinded rater scored outputs using a five-domain rubric (factual accuracy, clarity, policy compliance, call-to-action quality, structure/metadata; maximum score 10). Secondary measures included character count, hashtag use, and readability (Flesch-Kincaid Grade Level). General linear models with Bonferroni-adjusted post hoc tests and non-parametric analyses were applied. RESULTS: All four models achieved perfect factual accuracy and no policy violations. Mean total quality scores differed significantly by model, P < 0.001. GPT-5 (9.60) and Perplexity Pro (9.60) performed best, followed by Gemini 2.5 Pro (9.47), while Grok-3 scored lower (8.80). Domain analyses showed Grok-3 underperformed in call-to-action quality (1.40 vs. ≥1.97 in other models, P < 0.001) and produced significantly shorter posts (median 194 characters, P < 0.001). Perplexity Pro scored highest for policy compliance, while GPT-5 and Gemini 2.5 Pro achieved superior structural scores. Readability varied: GPT-5 8.9 (7.3-9.2) and Perplexity Pro 7.3 (6.5-8.8) generated more complex outputs, whereas Gemini 2.5 Pro 5.1 (4.8-6.5) and Grok-3 4.5 (3.6-6.3) produced more accessible posts. CONCLUSION: LLMs can reliably generate accurate and policy-compliant social media posts for research promotion, with differences in style and readability that may inform audience targeting. GPT-5, Gemini 2.5 Pro, and Perplexity Pro produced high-quality outputs, while Grok-3 underperformed across several domains. These findings highlight the potential of LLMs as scalable first-draft tools for post-publication promotion, capable of improving the reach and accessibility of scientific research. Careful model selection, tailored to audience and communication goals, together with human oversight, remains essential.
25 June 2026
Read appraisal →Journal of medical Internet research
Trusting Generative AI for Health Advice: Preregistered Survey Experiment
BACKGROUND: Generative artificial intelligence (AI) systems are increasingly used for health information seeking, yet it remains unclear how the public evaluates AI-generated health advice relative to guidance from credentialed clinicians in digital environments. Understanding the conditions under which AI is perceived as credible is critical as these systems become integrated into digital health ecosystems. OBJECTIVE: This study examined how source type (a human nurse in an online portal, a health care-specialized generative artificial intelligence system framed as an "AI nurse," or ChatGPT [OpenAI], a general-purpose chatbot), message characteristics, contextual risk, values framing, and individual differences in medical skepticism and experience with AI shape credibility evaluations of the provided advice and its purported source. METHODS: In a preregistered online experiment, a national sample of US adult participants (N=1502) was randomly assigned to 1 of 3 source conditions and evaluated health advice across 3 scenarios: low risk (dietary advice for cholesterol), high risk (chest pain triage), and a morally sensitive scenario (egg freezing). Advice type (intuitive vs counterintuitive) was manipulated in the risk scenarios, and ideological framing (neutral, conservative-leaning, and liberal-leaning) was manipulated in the morally sensitive scenario. Primary outcomes included participants' perceived credibility of the advice and beliefs about whether the patient should follow it. Source-level perceptions of competence and benevolence were also assessed. Medical skepticism and prior AI experience were examined as moderators. RESULTS: Advice attributed to a human nurse was rated as more credible than advice attributed to either AI source. Message intuitiveness showed effects comparable to, and sometimes larger than, the effects of source: intuitive advice was perceived as more credible than counterintuitive advice, with this difference amplified in high-risk contexts. In the morally sensitive scenario, ideological framing influenced perceived bias but did not interact significantly with source. Medical skepticism moderated source evaluations: higher skepticism was associated with greater perceived competence of the AI nurse and lower perceived competence of the human nurse. CONCLUSIONS: Generative AI is evaluated within existing credibility frameworks rather than dismissed outright as inferior to human expertise. While licensed clinicians retain a credibility advantage, AI-generated advice is generally perceived as competent and legitimate. Importantly, individuals skeptical of traditional medical authority may evaluate AI-based guidance more favorably, suggesting that AI systems may redistribute-rather than uniformly erode-trust in health advice. As AI tools become embedded in patient-facing health platforms, message design and audience characteristics may shape acceptance more strongly than source labeling alone.
24 June 2026
Read appraisal →Journal of affective disorders
Interventions to reduce loneliness in children and adolescents (4-18 years): A systematic review and meta-analysis with narrative synthesis of study-level characteristics
Loneliness in youth is linked to poor mental and physical health, yet the effectiveness of interventions remains unclear. Given its distinct developmental presentation, this meta-analysis synthesises interventions targeting loneliness in individuals aged 4-18 to inform age-appropriate strategies. It examines the effects of interventions on loneliness and includes a narrative synthesis of intervention and sample characteristics. We conducted a systematic literature review and meta-analysis of quantitative studies up to March 2024, focusing on interventions where loneliness was the primary target in school-aged youth. Nineteen studies were included in the SLR, of which 18 were included in the meta-analysis (6 RCTs, 6 multi-cohort, and 6 single-cohort studies). RCTs showed a small, non-significant reduction in loneliness (Hedges' g = -0.20, 95% CI [-0.42, 0.02], p = .07), with social and emotional skills training interventions being most effective. Multi-cohort studies showed a negligible effect (Hedges' g = -0.01, 95% CI [-0.08, 0.07], p = .84). Single-cohort studies indicated a moderate, non-significant effect (Hedges' g = -0.55, 95% CI [-1.29, 0.18], p = .14). Interventions targeting loneliness show promise in reducing loneliness, particularly when they incorporate social and emotional learning. Future research should integrate qualitative approaches and consider loneliness within broader mental health and well-being frameworks to support the development of more comprehensive, youth-centred interventions.
16 June 2026
Read appraisal →Journal of affective disorders
Prediction models for suicide reattempts by lasso regression through machine learning models: Single versus multiple suicide attempters.
The best predictor of a suicide attempt is a previous attempt, apart from psychiatric diagnoses also associated. Some studies found other indicators of great risk for suicide reattempts. Machine Learning algorithms offer the potential for systematic detection of features that carry greater risk for an event. This study sought to develop a classification algorithm distinguishing between Single Suicide Attempters (SSA) and Multiple Suicide Attempters (MSA) in a Spanish multicentre national cohort to explore prediction of subsequent attempts in suicidal patients. Two models including the same sociodemographic and clinical variables grouped in more specific (Model I) or broad (Model II) categories were developed to explore risk factors for suicide reattempts. A Least Absolute Shrinkage and Regression Operator logistic regression with a 10-fold cross-validation was adopted. 1443 adult patients from the SURVIVE cohort were included (582 SSA and 861 MSA). Both Model I (AUC = 0.696; BAC = 0.644) and Model II (AUC = 0.678; BAC = 0.621) outperformed naïve majority-class classification for SSA and MSA. Bipolar disorder type II, binge-eating disorder, and schizophrenia variables weighted heavier on Model I for suicide reattempt-related; while eating disorder diagnosis, Africa as birthplace, affective disorder diagnosis, being employed, schizophrenia-spectrum disorder and substance use disorder diagnoses were the most important suicide reattempt-related of Model II. Affective disorders, eating disorders and schizophrenia-spectrum disorders emerged as the most important variables in predicting reattempts. Both models showed similar sensitivity and specificity when discriminating between SSA and MSA. Identifying specific risk factors for reattempts could have a significant impact on tailoring prevention strategies and interventions.
16 June 2026
Read appraisal →Sexual health
A systematic review of barriers to cervical cancer screening among Thai women based on the social ecological model: a multi-level analysis of local evidence
BACKGROUND: Cervical cancer is a significant public health issue in Thailand. Despite the implementation of a national screening program, its coverage remains suboptimal. This study aims to systematically review local Thai evidence and comprehensively analyze the multi-level barriers affecting women's participation in cervical cancer screening using the social ecological model (SEM). METHODS: Systematic searches were conducted in PubMed, Scopus, CINAHL and ThaiJO databases from inception to 2025. Literature was screened according to pre-defined inclusion and exclusion criteria, resulting in the inclusion of 11 studies. The Newcastle-Ottawa scale and a mixed-methods assessment tool were used for rigorous quality appraisal. Thematic synthesis was used to categorize screening barriers into five levels: individual, interpersonal, community, health system and public policy. RESULTS: The key obstacles identified include: at the individual level, lack of knowledge, fear, shame and insufficient risk perception; at the interpersonal level, the influence of family and social norms; at the community level, cultural, religious and regional factors; at the health system level, poor service accessibility and system inefficiencies; and at the public policy level, incomplete health insurance coverage and insufficient awareness campaigns. Many of these obstacles show distinct characteristics of Thai society and culture. CONCLUSION: Barriers to cervical cancer screening among Thai women constitute a complex, multi-level system. Future intervention strategies must move beyond single-level health education, and should develop cross-level, culturally-appropriate, comprehensive measures. These include promoting HPV self-sampling, conducting community empowerment education, optimizing the health service system and strengthening policy support to systematically increase screening participation.
16 June 2026
Read appraisal →Sexual health
Digital versus clinic-based sexual health services: patterns of use and equity implications from a UK-based evaluation
BACKGROUND: Digital sexual health services have expanded rapidly in England; yet, concerns remain regarding equitable access among different population groups. We compared demographic characteristics and outcomes between online and clinic-based sexual health service users in Leicester, Leicestershire, and Rutland. METHODS: A retrospective analysis of data (April 2019-June 2023) compared online contacts, via SH:24, a UK online sexual health service providing postal sexually transmitted infection (STI) testing and remote contraception, with in-clinic attendances. Demographic variables included age, gender, ethnicity and Index of Multiple Deprivation (IMD 2019) decile, where Deciles 1-2 represent the most deprived areas. Ethnicity was recoded into Office for National Statistics categories. Reasons for attendance, contraception methods, and STI test outcomes were analysed. Risk ratios with 95% confidence intervals compared proportions between modalities. RESULTS: Online users were younger than clinic attendees (mean age, 25.1 vs 31.4 years). A slightly higher proportion of women accessed online services although gender was unrecorded in 59.1% of online attendances. White and mixed ethnicity groups were more likely to use online services than Black, Asian and 'Other' ethnic groups. Individuals living in the most deprived areas were less likely to access online services. STI testing was more frequent online (56.8% vs 43.3%), while positivity rates for infections were lower. CONCLUSIONS: Complementary to clinic-based sexual health services, online pathways provide accessible STI testing and contraception. Differences in uptake by age, ethnicity and deprivation highlight the importance of monitoring equitable access as digital provision expands. Maintaining both online and face-to-face provision is likely to remain important for equitable sexual health care.
16 June 2026
Read appraisal →Journal of hazardous materials
Biomarker-anchored screening of dietary microplastics via a gut microbiota-informed machine learning model
Microplastics (MPs) are increasingly recognized as emerging contaminants in the human diet, yet the absence of unified biomarker-anchored screening thresholds hampers quantitative risk assessment. This study establishes a gut microbiota-anchored machine learning framework that links Firmicutes/Bacteroidetes (F/B) ratio thresholds with real-world dietary MP exposure data, enabling a biomarker-anchored screening of dysbiosis-related signals associated with disease risk. Across the compiled disease cohorts, obesity provided the largest and most data-sufficient contrast in this dataset and was therefore selected as the anchor condition for threshold derivation. Receiver operating characteristic (ROC) analysis determined a model-derived screening cutoff for the F/B ratio (cutoff = 1.08), which was further used to define a three-tier risk classification system. A dataset comprising 558 dietary MP records from 129 studies across 25 countries was incorporated to predict food- and region-specific risk levels. Results reveal that seafood represents the dominant global dietary MP risk source, with mollusca contributing the highest predicted F/B-related risk signal. Spatial stratification indicates that the United States and Ecuador were classified into the highest model-derived tier based on national mean predicted F/B values, followed by high-risk regions such as Vietnam, Turkey, and Ireland, while countries in the Middle East and North Africa remain at moderate risk. These geographic contrasts suggest the combined influence of dietary structure and regional exposure intensity. Overall, we present a biomarker-anchored, machine-learning-enabled screening framework that links dietary MP exposure to predicted changes in a dysbiosis-associated indicator (F/B). This approach can support monitoring prioritization, identification of data gaps, and hypothesis generation for future validation studies.
15 June 2026
Read appraisal →Environmental research
Air pollution and adverse birth outcomes: A systematic review of fine critical windows
Epidemiological studies have reported associations between prenatal exposure to outdoor air pollution and adverse pregnancy outcomes. However, most analyses assessed exposure over the entire pregnancy or by trimester, potentially missing specific critical windows of vulnerability that recent statistical methods can identify. The objective of this study was to summarise studies examining critical windows of exposure to outdoor air pollution in relation to adverse pregnancy outcomes. This systematic review (PROSPERO-CRD42024523345) followed PRISMA recommendations using PubMed, Embase and CENTRAL databases. The search was performed on April 2024 and udpated on February 2025. Eligible studies analysed critical windows of association between air pollutants (PM2.5, PM10, NO2, O3) and the following outcomes: prematurity, low birth weight, intrahepatic cholestasis of pregnancy, gestational diabetes, pre-eclampsia, eclampsia, gestational hypertension and stillbirth. Two independent reviewers screened titles, abstracts and full texts. Results were synthesised narratively. Out of 3631 articles, 20 studies were included. All were conducted in China or the United States and relied almost exclusively on distributed lag models (DLM or DLNM). Heterogeneity was observed across pathologies and between studies addressing the same outcome. The most consistent finding concerned preterm birth, for which the end of the second trimester (weeks 17-28) was often identified as a critical window. No studies addressed intrahepatic cholestasis of pregnancy or stillbirth. Conclusions. The variability in results reflects distinct pathophysiological mechanisms, differences in exposure levels, or individual characteristics. Precisely identifying critical windows of environmental exposure during pregnancy appears essential to improve perinatal environmental prevention and guide public health action.
15 June 2026
Read appraisal →Journal of hazardous materials
Prenatal 6:2 Cl-PFESA exposure and birth weight: A systematic review and meta-analysis
Most existing systematic reviews and meta-analyses on PFAS have focused on legacy compounds, yet with less attention on PFAS alternatives and mixtures. Chlorinated polyfluorinated ether sulfonic acids (Cl-PFESAs) have been introduced as PFOS alternatives. Among these, 6:2 Cl-PFESA has accumulated persistent environmental residues and has recently emerged as a significant health concern. We aim to evaluate the association between prenatal 6:2 Cl-PFESA exposure and birth weight using a meta-analysis. A systematic review identified 12 studies reporting birth weight in relation to 6:2 Cl-PFESA biomarker measures, including maternal serum and umbilical cord samples. Risk of bias and study sensitivity were assessed, and overall effects were estimated by random-effects model. Stratified analyses were conducted by study confidence, sample size, and exposure level. The overall pooled estimate showed no statistically significant association between 6:2 Cl-PFESA exposure and birth weight. However, subgroup analyses revealed a consistent reduction in birth weight per ln-unit increase in 6:2 Cl-PFESA in studies with large sample sizes (β = -20.05 g; 95% CI: -33.13, -6.97), high methodological confidence (β = -16.74 g; 95% CI: -26.42, -7.06), or higher exposure levels (β = -16.15 g; 95% CI: -25.43, -6.87), all showing low between-study heterogeneity. Sensitivity analysis excluding the study contributing most to heterogeneity indicated a 15.57 g decrease in birth weight per ln ng/mL increase in 6:2 Cl-PFESA (95% CI: -24.74, -6.40). Although current evidence suggests that prenatal 6:2 Cl-PFESA exposure may adversely affect fetal growth, well-designed prospective studies with standardized exposure assessments are needed to confirm this potential risk.
15 June 2026
Read appraisal →Journal of global health
mHealth for chronic disease management: effects on adherence in Ghanaian patients with diabetes and hypertension
BACKGROUND: Medication non-adherence remains a major barrier to effective chronic disease management, particularly in low- and middle-income countries. In Ghana, limited access to continuous care and patient engagement tools contributes to poor adherence among individuals living with type 2 diabetes and hypertension. Mobile health interventions, including smartphone applications, may offer scalable solutions to support long-term medication use and self-management. Here, we assess the effect of a smartphone-based intervention on medication adherence among adults with these conditions. METHODS: We conducted a quasi-experimental study among 874 adults with type 2 diabetes or hypertension in Ghana. Participants were assigned to either a smartphone-based intervention, which included medication reminders, educational content, and self-monitoring tools, or standard care involving routine outpatient management and follow-up without access to the smartphone-based intervention. We measured medication adherence at baseline and six months using the Medication Adherence Rating Scale and assessed it through generalised estimating equations and difference-in-differences analyses, adjusting for baseline adherence, age, sex, and treatment setting. RESULTS: Use of the smartphone application was associated with a greater improvement in medication adherence over six months in the overall study population (adjusted beta coefficient (aβ) = 0.062; 95% confidence interval (CI) = 0.010-0.123). Similar improvements were observed among participants with type 2 diabetes (aβ = 0.067; 95% CI = 0.012-0.135) and hypertension (aβ = 0.068; 95% CI = 0.005-0.134). However, there was no statistically significant difference in adherence between the intervention and control groups at six months. CONCLUSIONS: Smartphone-based interventions were associated with modest improvements in medication adherence over time, although between-group differences at follow-up were not statistically significant. As access to mobile technology expands across Africa, such interventions may provide scalable strategies to support chronic disease management.
14 June 2026
Read appraisal →BMJ paediatrics open
Smartphone-based support for early childhood development in a rural low-resource setting: an individually randomised pilot feasibility trial from Guatemala
OBJECTIVE: To test the feasibility of a smartphone app, BebeApp, that provides evidence-based early childhood development (ECD) guidance in rural Guatemala and pilot procedures for an adequately powered randomised controlled trial. DESIGN: We conducted an individually randomised pilot feasibility trial to compare BebeApp to printed ECD guidance. SETTING: This trial was conducted in Tecpán, Chimaltenango, a semi-rural community that is 95% Kaqchikel Indigenous Maya. PATIENTS: First-time primary caregiver-infant (0-28 days) dyads. INTERVENTIONS: BebeApp provides age-dependent, evidence-based caregiver guidance for breastfeeding and complementary feeding, sleep and developmental support. MAIN OUTCOME MEASURES: A mixed-methods evaluation of BebeApp's implementation and acceptability using the Reach, Effectiveness, Adoption, Implementation, Maintenance framework. App usability, usefulness and satisfaction were assessed via questionnaires, semi-structured interviews and app interaction data. RESULTS: 41 infant-caregiver dyads were enrolled with 40 completing the study. Engagement was high with caregivers opening BebeApp a median (IQR) 11 (6-21) times per month. Usability was found to be acceptable but no difference was found between pre-measurements and post-measurements. In interviews, caregivers expressed some initial difficulty using BebeApp but were able to gain confidence with a training session. App usefulness and satisfaction responses were positive. Caregivers often noted that BebeApp was their only source of ECD information outside of their family. CONCLUSIONS: We found that caregivers in rural Guatemala responded positively to a smartphone ECD app and engaged with it throughout the trial. Given the urgent need for ECD programmes in low- and middle-income settings, smartphone apps may be a method to deliver services directly to caregivers.
14 June 2026
Read appraisal →BMC cardiovascular disorders
Trends in cardiac implantable electronic device infections: 2015 to 2019
BACKGROUND: Cardiovascular implantable electronic devices (CIEDs) improve survival in patients with cardiac rhythm disorders but carry risks of complications, most notably major infections. Reported infection rates vary internationally, and contemporary large-scale data from Germany are scarce. We aimed to determine nationwide rates of CIED infection-related hospitalizations and associated mortality over a five-year period. METHODS: We analyzed administrative claims from Germany's largest statutory health insurer covering more than 27 million beneficiaries. All CIED procedures performed between January 2015 and December 2019 were identified, including initial implantations, upgrades or downgrades, generator replacements, early revisions, and device extractions. Major infections were detected using International Classification of Diseases (ICD-10-GM) and procedural codes, and stratified as generator pocket infections or lead-associated endocarditis. In-hospital mortality was determined from discharge records. RESULTS: Among 282,205 patients (57.7% male) undergoing CIED procedures, 6,577 individuals (2.33%) experienced 7,704 major infections within three months. Generator pocket infections occurred in 5,396 cases (1.91%), lead-associated endocarditis in 2,308 (0.82%), and combined infections in 1,127 patients (0.39%) within the acute 90-day observation period. CIED infections substantially increased healthcare utilization: Infected patients required substantially more procedures than non-infected patients, despite correct treatment. In-hospital mortality reached 8.36% for pocket infections and 15.0% for endocarditis. Extended follow-up in the 2015 cohort revealed a 4.33% infection-related procedure rate over five years. CONCLUSIONS: Nationwide German data reveal higher acute CIED infection rates than previously reported, with considerable mortality and procedural burden. These findings highlight an urgent need for improved prevention and management strategies.
14 June 2026
Read appraisal →Journal of medical Internet research
Telehealth Usability, Engagement Patterns, and Technical Infrastructure in Managing Noncommunicable Diseases Among Health Care Professionals in Brazil, Ghana, Honduras, and the United Kingdom: Multinational Cross-Sectional Study
BACKGROUND: Noncommunicable diseases (NCDs) account for over 70% of global deaths, with hypertension and diabetes serving as major contributors. The COVID-19 pandemic disrupted traditional health care services for NCDs and highlighted telehealth as a crucial alternative. Telehealth-encompassing synchronous and asynchronous electronic communication to deliver clinical services remotely-can overcome geographical barriers and enhance patient engagement. However, telehealth usability among health care professionals (HCPs) remains under-studied across low-, middle-, and high-income countries. OBJECTIVE: This study aimed to examine which telehealth engagement patterns, technical infrastructure factors, and user profiles were most strongly associated with usability among HCPs and to descriptively compare these across 4 diverse countries: Brazil (high- to middle-income country), Ghana (low- to middle-income country), Honduras (low- to middle-income country), and the United Kingdom (high-income country). METHODS: A multinational cross-sectional survey was conducted with 290 HCPs across 4 countries. Participants completed the System Usability Scale and provided data on telehealth engagement (eg, frequency, duration, and number of systems used), technical infrastructure (connection stability and support satisfaction), and their user profile (demographics, job role, and training received). Descriptive statistics summarized these patterns and usability scores. Multiple linear regression with bootstrap-based sensitivity analyses identified factors associated with telehealth usability. Given the nonprobability design, no formal inferential comparisons were made between countries. Instead, observed patterns were reported descriptively. RESULTS: Higher telehealth usability scores were associated with greater connection stability (b=5.06, 95% CI 3.06-7.05), higher satisfaction with online support information (b=5.02, 95% CI 3.27-6.75), more frequent use (b=3.05, 95% CI 1.36-4.73), longer duration of use (b=1.59, 95% CI 0.49-2.68), and being a physician by profession (b=3.82, 95% CI 0.23-7.40). Average usability scores were highest among users in Ghana (mean 79.75, SD 14.19) and the United Kingdom (mean 79.00, SD 14.71), followed by Brazil (mean 72.01, SD 14.62) and Honduras (mean 63.09, SD 15.57). According to System Usability Scale guidelines, scores corresponded to "good" usability for users in Ghana, the United Kingdom, and Brazil and were below the "good" threshold for users in Honduras. While most users in Ghana (97/111, 87.4%), Honduras (31/38, 81.6%), and Brazil (57/80, 70.4%) reported using only 1 telehealth system, two-thirds of UK users (40/60, 66.7%) reported using 2 or more systems. User profiles also varied; prepandemic use was highest in Ghana (84/111, 75.7%) and lowest in Honduras (7/38, 18.4%). Other engagement patterns across countries were reported. CONCLUSIONS: Telehealth usability is driven by technical infrastructure reliability, a robust online support infrastructure, and an "experience effect" from frequent and long-term engagement. Descriptive differences in engagement patterns and infrastructure highlight the need for tailored strategies to address setting-specific challenges. These are essential to optimize telehealth integration and improve health care outcomes for patients with NCDs worldwide.
14 June 2026
Read appraisal →BMC geriatrics
The association between smart elderly care and subjective well-being among older adults in China: the mediating roles of health status and social activities
BACKGROUND: Under the initiative of China's "Internet+" strategy, smart elderly care reflects the government's capacity to bridge the digital divide and provide inclusive care services for older adults. Though studies have identified positive associations between smart elderly care and health outcomes, empirical research examining its impact on older adults' subjective well-being remains limited. METHODS: This study utilizes data from the 2021 Chinese Longitudinal Healthy Longevity Survey (CLHLS, N = 8,950), which includes multifaceted information on individuals aged 65 and above, covering their personal characteristics, health status, family information, and community elderly care services. A logit model is employed to investigate the association between smart elderly care and SWB. The mediating effects are tested using the bootstrap resampling method. To address endogeneity concerns, instrumental variable (IV) approaches including IV-Probit and 2SLS are applied as robustness checks. RESULTS: The results reveal a positive correlation between smart elderly care and older adults' subjective well-being (β = 0.101, p < 0.01). This association is partially mediated by both health status (proportion mediated: 38.47%) and social activities (proportion mediated: 2.65%). Heterogeneity analyses show that this positive association holds consistently across both rural and urban older adults, and is more pronounced among those with lower digital literacy. CONCLUSIONS: This study challenges the prevailing assumption that the "digital divide inevitably isolates the older adults from participating in a digitized society." By integrating digital technologies into older adults care services, we demonstrate that smart elderly care is positively associated with bridging technological barriers and addressing the unmet needs of aging populations. These findings further propose a synergistic mechanism-policy innovation, technological adaptation, and service optimization, to build an inclusive older adults care ecosystem, offering evidence-based insights for policymakers in aging societies to balance equity and efficiency in digital transformation.
14 June 2026
Read appraisal →BMJ open
Barriers and facilitators to digital health tool adoption for hypertension management: systematic review of qualitative studies
OBJECTIVES: Digital health interventions (DHIs) show considerable promise in supporting hypertension self-management by promoting preventative care and self-monitoring. While their efficacy is increasingly evident, the long-term uptake, acceptance and sustained engagement with these tools are frequently challenged by issues such as usability, trust and varying user experiences. This review aims to synthesise qualitative evidence to identify barriers and facilitators and the key factors that impact the adoption, acceptance and engagement with DHIs for hypertension self-management. DESIGN: Systematic review of qualitative literature using thematic analysis following Cochrane's qualitative and implementation methods guidance. DATA SOURCES: PubMed, PsycInfo, Web of Science and the Cochrane Library were searched in February 2025. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: The searches included relevant qualitative and mixed-methods studies on the use of digital devices for hypertension management, which described the barriers and facilitators associated with these tools. We included studies published from 2015 to 2025 to capture relevant evidence. Only studies published in English with a qualitative approach were included. RESULTS: From an initial 10 943 identified publications, 15 met our inclusion criteria, primarily originating from Europe and the USA, exploring diverse racial and ethnic group experiences. Our thematic synthesis revealed 7 analytical and 22 descriptive themes detailing barriers and facilitators encountered by patients with hypertension, healthcare providers (HCPs) and caregivers. These themes covered technology utilisation, design components, linguistic and cultural relevance, healthcare factors, trust and credibility and interpersonal interactions. CONCLUSION: Our analysis underscores that factors such as the usability, design and relevance of social support profoundly influence the uptake and acceptance of DHIs in hypertension self-management among patients, caregivers and HCPs. PROSPERO REGISTRATION NUMBER: CRD42023480389.
14 June 2026
Read appraisal →JMIR public health and surveillance
Digital Health Center App for Community and National Malaria Surveillance in Cambodia: Implementation Case Study
BACKGROUND: By 2015, the emergence and dissemination of multidrug-resistant Plasmodium falciparum in the Greater Mekong Subregion threatened regional and global malaria control efforts. In response, Greater Mekong Subregion countries committed to malaria elimination by 2030, with strengthened surveillance as a strategic pillar. In 2017, Cambodia introduced an elimination-oriented digital Malaria Information System (MIS). Its health center app enables real-time, geo-located, case-based malaria reporting across primary health centers, and is fully integrated with the MIS. OBJECTIVE: This study aimed to evaluate the real-world national implementation of Cambodia's Android-based health center app, considering coverage, fidelity, timeliness, and data use, and their effects on malaria surveillance performance, case management, programmatic response, and public health outcomes. METHODS: System performance and public health use were assessed using system-generated metadata, national surveillance data, and user surveys. Operational indicators included technical performance, data completeness, and reporting timeliness, alongside surveillance outcomes such as case notification, classification, reactive case detection, and foci investigation. Nationwide user experience was measured via a survey of 761 health centers across 21 provinces, with in-depth structured surveys at 9 health centers in 3 provinces. Descriptive analyses evaluated system functionality, contribution to malaria surveillance and response, and usability among frontline health workers. RESULTS: The health center app demonstrated strong technical performance, with rapid loading and resilient data transmission under low-bandwidth conditions, supporting reliable reporting in resource-constrained settings. Integrated real-time dashboards provided analytics for case management, surveillance monitoring, risk stratification, and targeted public health interventions. Data completeness remained high (99%, 89/90 fields in 2024), demonstrating consistent routine use even as case incidence declined. Between January 1, 2025, and July 31, 2025, 69 malaria cases were reported nationally (23 locally acquired, 7 domestically imported, and 39 internationally imported). Of these, 95.7% (66/69) were notified and classified within 1 day. Reactive case detection was completed within 3 days for all 21 eligible cases, and 16 of 19 eligible foci received a response within 7 days, indicating strong operational responsiveness. User surveys showed 96.3% (733/761) of health centers were satisfied or very satisfied, 90.1% (686/761) reported rare or no technical issues, and 91.7% (698/761) found the app easy to navigate. Operational challenges included limited internet connectivity, transport to remote areas, and electricity interruptions. In-depth surveys confirmed high uptake, confidence in reporting, and routine use of surveillance data, although gaps in local analytical capacity were identified. CONCLUSIONS: Developed and managed locally to enhance sustainability, the MIS drove significant reductions in malaria case incidence, with the health center app contributing timely, complete, structured reporting at the point of care. Public health responses were facilitated by real-time analysis, targeted interventions, and decentralized decision-making. User engagement was sustained as malaria cases declined, and further enhancements are planned to ensure seamless transition to postelimination surveillance, reducing the risk of malaria reestablishment in Cambodia.
13 June 2026
Read appraisal →BMJ (Clinical research ed.)
Low concentration atropine eye drops and progression of myopia in children: multicentre placebo controlled, double masked, randomised trial in the UK (CHAMP-UK)
OBJECTIVES: To evaluate the efficacy and safety of low concentration atropine eye drops for reducing progression of myopia in children in the UK. DESIGN: Multicentre, double masked, superiority, placebo controlled, randomised trial. SETTING: National Health Service hospital eye services and academic institutions at five UK centres. PARTICIPANTS: 289 children aged 6-12 years with myopia between -0.50 and -10.0 dioptres (D). Participants were allocated in ratio of 2:1 to atropine or placebo. INTERVENTIONS: One eye drop of preserved atropine 0.01% or placebo daily for two years. MAIN OUTCOME MEASURES: The primary outcome was spherical equivalent refractive error of both eyes measured by autorefractor under cycloplegia after two years. Secondary outcomes included change in axial length, best corrected distance and near visual acuity, reading speed, pupil diameter, spectacle correction, adverse event rates, quality of life, and tolerability. Outcomes were collected every six months. An electronic monitoring system was used to assess adherence. RESULTS: 192 participants were included in the atropine group and 97 in the placebo group, with an average age of 9.3 years (standard deviation (SD) 1.7 years). 207 (72%) reported white ethnicity, 161 (56%) were girls, and the mean level of myopia was -2.87 D (SD 1.71 D). A total of 235 (81%) participants completed the study, with primary outcome data available for 230 (80%) participants: 151 (79%) in the atropine group and 79 (81%) in the placebo group. Atropine eye drops were more effective than placebo in reducing myopia progression (mean difference 0.33 D, 95% confidence interval (CI) 0.17 to 0.49 D, P<0.001). Prespecified subgroup analyses did not show differences according to age, ethnicity, sex, or severity of myopia. Changes in central axial length were significantly less in the atropine group versus placebo group: mean difference 0.14 mm (95% CI 0.07 to 0.21, P<0.001). There were no differences in other secondary outcomes, except pupil diameter, which was greater in the atropine group (0.36 mm, 95% CI 0.17, 0.55, P<0.001), and no differences in frequency of adverse events or in tolerability measures. No serious adverse events were related to the trial drugs. CONCLUSIONS: Low concentration atropine (0.01%) eye drops significantly reduced progression of myopia and were well tolerated compared with placebo in children in the UK. TRIAL REGISTRATION: ISRCTN registry ISRCTN99883695, ClinicalTrials.gov NCT03690089.
13 June 2026
Read appraisal →PloS one
Effects of a school-based ACT program on motivation, physical activity participation, motor competence, and physical performance in physically inactive female adolescent students
Adolescents face internal barriers like low self-confidence and psychological discomfort that limit physical activity. Adolescence offers a key window to enhance intrinsic motivation. Acceptance and Commitment Therapy (ACT) may effectively improve physical activity and motor competence through psychological flexibility and value-based behavior. This study examined the effects of an ACT-based intervention on physical activity participation, motivation, motor competence, and physical fitness in physically inactive adolescent girls. A randomized controlled trial involved 132 inactive girls aged 13-18, randomly assigned to either an ACT intervention or a control group. Intervention included seven sessions targeting six core ACT processes. Pre-and post-intervention assessments used standardized questionnaires and tests for physical activity participation, motivation, physical activity, motor competence, and fitness. ACT group showed significant improvements in intrinsic motivation, identified regulation, autonomy, and reduced amotivation and external regulation (p ≤ 0.05). Introjected regulation did not show a significant change (p > 0.05). Physical activity participation and fitness performance also improved significantly, along with both perceived and actual motor competence (p ≤ 0.05). ACT-based intervention effectively enhanced motivation, physical activity engagement, motor competence, and fitness. These findings support integrating ACT into school or community programs to promote sustainable physical activity habits in adolescent girls.
13 June 2026
Read appraisal →Journal of epidemiology and community health
Role of socioeconomic status in modifying the relationship between alcohol use and injury events: evidence from the UK Biobank
BACKGROUND: Alcohol consumption is a well-established risk factor for injuries, yet the role of socioeconomic status (SES) in modifying this relationship remains underexplored. This study examines how SES influences the association between alcohol use and injury events, including both fatal and non-fatal injuries as well as the risk of repeated injuries requiring hospitalisation. METHODS: Using data from the UK Biobank, we applied Cox proportional hazards models to assess whether SES modifies the relationship between different dimensions of alcohol use, average level and heavy episodic drinking (HED), and injury events. For injuries requiring hospitalisation, we fitted negative binomial regression models to estimate incidence rate ratios (IRRs) for the total number of unique injury admissions per individual. RESULTS: Among 482 078 participants, 48 045 injuries were recorded during follow-up. A statistically significant interaction was observed between alcohol use and low education, with individuals in lower education groups showing elevated injury risk compared with the high education group, particularly among those consuming 20-40 g/day with HED (HR: 1.17, 95% CI 1.06 to 1.28) and those consuming over 40 g/day (HR: 1.13, 95% CI 1.04 to 1.23). For non-fatal injuries, similar statistically significant interactions were found (IRR 1.17, 95% CI 1.06 to 1.28; and 1.18, 95% CI 1.08 to 1.29, respectively). CONCLUSION: Our findings highlight that individuals with lower SES face higher risks of alcohol-related injuries. Future research should investigate specific mechanisms underlying these disparities to inform more targeted policies. Population-based pricing policies could be combined with community-based programmes and tailored health messaging to address SES-related vulnerabilities.
13 June 2026
Read appraisal →The Journal of clinical psychiatry
Placebo Effects in Alcohol, Cocaine, and Methamphetamine Use Disorder: A Systematic Review and Meta-Analysis
Objective: The placebo effect is established in psychiatry, yet its role in substance use disorders (SUDs) treatment remains unclear. The aim of this study was to evaluate changes in craving scores in placebo groups in randomized controlled trials (RCTs) across different SUDs in adults. Data sources: Eight different databases (PubMed, Embase, Web of Science, Cochrane Library, Emcare, MEDLINE, PsycINFO, and Academic Search) were systematically searched up to October 28, 2024, by 2 independent researchers. Study selection: Placebo-controlled, double-blind RCTs assessing craving in patients with SUDs were included based on predefined eligibility criteria, published in English, Dutch, Spanish, or German language. Search terms were a combination and synonyms of "craving," "addiction," and "placebo." From a total of 1945 unique records identified, 9 articles met our eligibility criteria. Data extraction: Data on demographic characteristics, study design, and outcome results were extracted. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated for pre-post craving scores within each placebo group; a positive difference point towards improvement in the postplacebo period. Results: A total of n=495 placebo-treated participants were included from nine RCTs in three different SUDs (n=300 in alcohol, n=88 in cocaine, and n=107 in methamphetamine use disorder). Craving scores significantly decreased over time (meaning symptom improvement) in the placebo treatment group in alcohol use disorder (5 studies, SMD=0.93 [95% CI=0.33 to 1.54]) but did not reach statistical significance in cocaine use disorder (2 studies, SMD=0.61 [95% CI=-1.41 to 2.62]) or in (meth)amphetamine use disorder (2 studies, SMD=0.44 [95% CI=-3.43 to 4.32]). Conclusions: Placebo treatment led to reductions in craving scores across all three SUDs, although statistical significance was achieved only in alcohol use disorder. Given the low number of studies for cocaine and (meth)amphetamine use disorder, these estimates were captured with much uncertainty. These findings may inform the design of future RCTs and support the development of more individualized treatment approaches in clinical settings.
13 June 2026
Read appraisal →Human vaccines & immunotherapeutics
Safety and immunogenicity of a booster dose of COVAC-2, a Sepivac SWE™ adjuvanted SARS-CoV-2 recombinant protein vaccine in previously vaccinated healthy adults; a randomized controlled multicentre trial.
This Phase 1 clinical trial evaluated the safety and immunogenicity of COVAC-2, a recombinant protein subunit vaccine as a heterologous booster in adults previously immunized with authorized COVID-19 vaccines (NCT05226702). COVAC-2 contains the SARS-CoV-2 S1 spike protein subunit adjuvanted with Sepivac SWE™, an open-access oil-in-water adjuvant. Sixty participants were randomized to receive a single intramuscular dose of COVAC-2 (10 µg or 25 µg) or placebo, with follow-up through Day 180. The vaccine was well tolerated, with most adverse events being mild or moderate; no serious adverse events were attributed to vaccination. Immunogenicity assessments included spike-binding antibody ELISA, pseudovirus neutralization assays (PNA), ELISpot, and flow cytometry. The 25 µg dose elicited the strongest humoral and cellular responses, with peak antibody titers observed 14 d after COVAC-2 vaccination. While titers waned, they were sustained above baseline through Day 180. ELISpot and flow cytometry revealed elevated IFN-γ and IL-2 responses indicating antigen-specific T-cell activation. Minimal IL-4 and IL-13 responses were demonstrated by flow cytometry. These findings support the safety and immunogenicity of COVAC-2 as a heterologous booster, particularly at the 25 µg dose level. The favorable safety profile, induction of immune responses, and thermal stability of the vaccine formulation suggest its potential utility in global vaccination strategies, especially in low- and middle-income countries. COVAC-2 may offer a scalable and accessible platform for enhancing protection against COVID-19.Clinicaltrials.gov: NCT05226702 - Registered 22 Jul 2022.
13 June 2026
Read appraisal →JMIR formative research
Usability, Relevance, and User Engagement of a Government-Sponsored and Community Co-Designed Digital Mental Health Website During the COVID-19 Pandemic: A Pilot Study on Latino/a/x Adults
BACKGROUND: Latino/a/x adults have higher rates of unmet mental health needs than other racial and ethnic groups. One promising solution to help bridge this gap in care is digital mental health tools. Digital tools, such as self-help websites, have demonstrated the ability to enhance mental health literacy, reduce stigma, and improve mental health symptoms. Despite the potential benefits, engagement remains a critical challenge, and there has been a large oversight of unique considerations for Latino/a/x adults as end users. OBJECTIVE: Guided by the Technology Acceptance Model and the Behavioral Model for Vulnerable Populations, the study's overarching objective is to characterize within-group variation of Latino/a/x adults' engagement with a government-funded, prevention-focused mental health website that was co-designed with community partners during the COVID-19 pandemic. METHODS: The Together for Wellness/Juntos Por Nuestro Bienestar (T4W/Juntos) website offered free digital mental health resources to help Californians cope with the COVID-19 pandemic. A pilot evaluation of the website involved baseline and 4-week follow-up surveys about demographics, behavioral health needs, and overall website user experience. This current subanalysis focused on a stratified sample of Latino/a/x adult participants (baseline N=131; baseline and follow-up n=68). The baseline sample was mostly female (106/130, 81.5%); 66.9% (87/130) preferred to use the website in English and 30% (39/130) preferred Spanish. Behavioral health needs were assessed using the Patient Health Questionnaire-2, Generalized Anxiety Disorder 2-item scale, and a COVID-19 stressors checklist. We measured usability, comfort using the website, relevance of the website, and past-month use of resources. Data were analyzed using ordered and standard logistic regression methods. RESULTS: Latino/a/x adults who preferred using the website in English (odds ratio [OR] 13.76, P<.001) compared with Spanish were more comfortable using the website. Compared with adults aged 18-30 years, adults aged 41-50 years had significantly lower odds of agreeing that the website was easy to use. Sensitivity analyses revealed that participants who found the website easier to use (OR 2.22, P=.001) and those with greater behavioral health needs (OR 1.22, P=.045) were more likely to perceive the website's topics as relevant. Participants with higher behavioral health needs at baseline were more likely to use the website and engage with resources for anxiety or stress at follow-up (OR 1.42, P=.047). CONCLUSIONS: This study addresses gaps in understanding Latino/a/x adults' experiences with a prevention-focused mental health website. The language-based disparity in comfort highlights the need to significantly improve the user experience for Latino/a/x Spanish speakers. Still, the website can be a helpful resource for Latino/a/x adults with high behavioral health needs, bridging a critical gap in support. A collaborative approach to developing resource-rich websites with trusted community organizations is vital for effectively reaching Latino/a/x communities and tailoring resources to address their unique needs.
12 June 2026
Read appraisal →Vaccine
Immunogenicity and safety of Sabin-strain inactivated poliovirus vaccine in infants: a systematic review and meta-analysis
BACKGROUND: Poliomyelitis remains a threat to children under five despite global vaccination efforts. The Sabin-strain inactivated poliovirus vaccine (sIPV) has emerged as a safer alternative to conventional Salk-strain IPV (cIPV) due to lower biosafety requirements. This systematic review and meta-analysis evaluated the immunogenicity and safety of sIPV compared with cIPV in healthy infants completing the primary IPV series. METHODS: PubMed, Embase, Scopus, and Cochrane Library were searched for RCTs. Outcomes included seroconversion rates, seroprotection rates, geometric mean titers (GMTs), and adverse events. Data were pooled using random-effects models, and evidence certainty was assessed using RoB 2.0 and GRADE. RESULTS: Seven RCTs with 4646 infants were included. Seroconversion rates were comparable: PV1 100% (RR 1.00, 95% CI 1.00-1.01), PV2 102% (RR 1.02, 95% CI 0.98-1.07), PV3 100% (RR 1.00, 95% CI 0.99-1.01). GMTs were higher for sIPV after PV1 (MD 1.50, 95% CI 0.98-2.02) and PV2 (MD 0.52, 95% CI 0.06-0.98). Local adverse events were similar (OR 1.27, 95% CI 0.95-1.71), while systemic adverse events were higher with cIPV (OR 1.36, 95% CI 1.15-1.60). Fever (OR 1.50, 95% CI 1.20-1.87) and allergic reactions (OR 2.19, 95% CI 1.02-4.69) were slightly more frequent with sIPV. CONCLUSIONS: sIPV provides immunogenicity comparable to cIPV with an acceptable safety profile in infants. Its lower biosafety requirements support its use in global polio eradication programs.
11 June 2026
Read appraisal →Human vaccines & immunotherapeutics
Safety and immunogenicity of 4CMenB and MenACWY-CRM meningococcal vaccines when administered concomitantly in healthy adolescents: A phase 3b, randomized, observer-blind study.
Meningococcal vaccination of adolescents/young adults is recommended in various countries, including the United States (US). This phase 3b, observer-blind study (NCT04318548) evaluated the safety, reactogenicity, and immunogenicity of serogroup B vaccine, 4CMenB, and quadrivalent conjugate vaccine, MenACWY-CRM, when co-administered to healthy individuals aged 16-18 y, as per US Advisory Committee on Immunization Practices recommendations. Adolescents, who had received MenACWY vaccination ≥4 y previously, were randomized (N = 940; 1:1:1) to one of three groups to assess co-administration versus 4CMenB and MenACWY-CRM administered alone. Co-primary objectives were to demonstrate the non-inferiority of antibody responses after concomitant administration to antibody responses after 4CMenB (two doses administered 2 months apart) and MenACWY-CRM (single dose), as measured by human serum bactericidal assay (hSBA). Vaccine safety and reactogenicity were assessed as another primary objective. The co-primary endpoints were met: the lower limit of 2-sided 95% confidence intervals for all between-group ratios of hSBA geometric mean titers was >0.5 for the concomitant administration group versus 4CMenB group and MenACWY-CRM group. hSBA data after two 4CMenB doses and one MenACWY-CRM dose showed comparable between-group geometric mean ratios versus baseline, and percentages of participants with 4-fold rises in titers and titers ≥lower limit of quantitation. The safety profile of 4CMenB co-administered with MenACWY-CRM was comparable with that of 4CMenB administered alone. In conclusion, 4CMenB and MenACWY-CRM co-administration was well tolerated in adolescents aged 16-18 y and immune responses were comparable versus administration of each vaccine alone, which is consistent with a previous study of co-administration in infants. Invasive meningococcal disease, caused by the bacterium Neisseria meningitidis, poses a life-threatening risk but can be prevented through vaccination. Effective vaccines are available against the most common disease-causing meningococcal serogroups, A, B, C, W, and Y. Evidence from clinical studies and immunization programs over the last decade with the 4-component meningococcal serogroup B vaccine, 4CMenB, and serogroups A, C, W, and Y vaccine, MenACWY-CRM, confirms the effectiveness of both vaccines in population age groups at higher risk of meningococcal disease, including infants and adolescents. It was previously shown that the administration of 4CMenB and MenACWY-CRM to healthy infants at the same visit induced good immune responses and was well tolerated by young children. Adolescent vaccination with 4CMenB and MenACWY-CRM is recommended in various countries, including in the United States. We conducted a study to test the safety of concomitant administration and its ability to induce immune responses in 945 healthy adolescents aged 16–18 y; 834 from the United States and 111 from Italy. We found that most reactions to the 4CMenB and MenACWY-CRM injections were mild or moderate, and were similar whether the vaccines were given together or separately, with no unexpected side effects. Co-administration to adolescents induced robust immune responses against serogroup B and serogroups A, C, W, and Y. These results support the use of concomitant meningococcal vaccinations in adolescent immunization programs.
11 June 2026
Read appraisal →Global health action
mHealth-supported tuberculosis contact investigation by community health workers in high-burden countries: a scoping review
Mobile health (mHealth) implementation strategies in tuberculosis (TB) contact investigations are intended to increase community health workers' (CHWs) engagement in TB contact investigations and case detection. This scoping review aimed to map and synthesize existing evidence on the design and development of acceptable and feasible mHealth implementation strategies for CHW-led TB contact investigations. We conducted a scoping review following the Arksey and O'Malley framework and PRISMA-ScR guidelines. We searched PubMed, Scopus, Cochrane Library, Web of Science, and Google Scholar for English-language studies published through October 2024 on mHealth interventions for TB contact investigation by CHWs. Eligible studies included empirical studies conducted in high-burden countries (HBCs) for TB, HIV-associated TB, and MDR/RR-TB. Studies were screened, and data were extracted using Rayyan AI-assisted software. We mapped implementation strategies, barriers, facilitators, acceptability, and feasibility of mHealth interventions. Quantitative findings were described, and qualitative data were synthesized thematically. Nine studies were included. Most interventions used hybrid mHealth technologies for communication, case registration, health records, and decision support. Implementation strategies specified actors, actions, targets, temporality, dose, and justifications. Barriers were related to CHWs, digital systems, service implementation, and TB-affected persons. Facilitators included stakeholder support, CHW training, mHealth design, community engagement, and patient-centered approaches. Overall, CHWs perceived mHealth interventions as acceptable and feasible. Successful implementation in HBCs requires strengthened CHW capacity, reliable technology, optimizing interaction between CHWs and digital tools, and continuous monitoring and evaluation throughout implementation. Main findings: Health interventions for tuberculosis contact investigation by community health workers in three global lists of high-burden countries for tuberculosis, human immunodeficiency virus-associated tuberculosis, and multidrug-resistant/rifampicin-resistant tuberculosis are generally acceptable and feasible, but their effectiveness depends heavily on a clear implementation strategy and the ability to address multilevel barriers at the individual, technology, and service system levels.Added knowledge: Given the ongoing development of digital health interventions for TB contact investigation by community health workers, this review provides a novel contribution by systematically mapping seven dimensions of implementation strategies, classifying barriers and facilitators at multiple levels, and highlighting the importance of synergies between human actors and digital systems in determining implementation success.Global health impact for policy and action: These findings confirm that strategic integration of mHealth into national tuberculosis policies and programs – with sustained funding, community health worker capacity building, digital system interoperability, and implementation-based monitoring – is crucial for closing the contact investigation gap and accelerating the achievement of the global tuberculosis elimination target.
11 June 2026
Read appraisal →Blood advances
Accurate identification of sickle cell disease cases in a large genotyped cohort using electronic health record data
The US Food and Drug Administration recently approved sickle cell disease (SCD) gene therapies that require a contemporaneous cohort to compare their outcomes with those of individuals who did not receive gene therapy. Previously, we developed an automated algorithm to create a contemporaneous cohort of children and adults with SCD using electronic health record data. We tested the hypothesis that the updated Vanderbilt University Medical Center (VUMC) algorithm can identify individuals with SCD with sensitivity and specificity of >95%. In the VUMC health care system, we identified a cohort of 33 141 adults and children of primarily African ancestry who underwent β-globin gene sequencing, with a 1.4% prevalence of SCD (473/33 141). For SCD, the performance of the VUMC algorithm using International Classification of Diseases (ICD) and laboratory data showed a sensitivity of 97.6% (462/473), specificity of 99.9% (32 663/32 668), positive predictive value of 98.9% (462/467), and negative predictive value of 99.9% (32 663/32 674). Three SCD phenotypes account for 98.5% of the individuals in the cohort. The cohort had sensitivities of 96.8% (272/281), 93.7% (136/145), and 85% (34/40) for hemoglobin SS (HbSS)/Hb Sβ0-thalassemia (HbSβ0), HbSC, and HbSβ+, respectively. The cohort had a specificity of 99.9% across all 3 phenotypes: HbSS/HbSβ0, HbSC, and HbSβ+, respectively. We have developed an updated algorithm using ICD and laboratory data that accurately identifies individuals with SCD within a large health care system, and distinguishes HbSS/HbSβ0, HbSC, and HbSβ+.
9 June 2026
Read appraisal →Environmental monitoring and assessment
YOLO-geochemical integration for real-time aeolian dust monitoring: a critical review of signatures, health risks, and policy implications
Aeolian dust is one of the most pervasive natural air pollutants, strongly influencing atmospheric chemistry, visibility, climate feedback, and human health. This review critically evaluates the integration of geochemical fingerprinting techniques and YOLO-based deep learning frameworks for real-time aeolian dust monitoring, with the overarching objective of advancing source attribution, health risk assessment, and evidence-based policy formulation in dust-prone regions. The Middle East, particularly the Qatar Peninsula, experiences recurrent dust storms that transport mineral particles and trace metals, contributing to degraded air quality, reduced solar energy efficiency, and elevated risks of respiratory and cardiovascular diseases. Traditional monitoring approaches including satellite observations, ground-based measurements, and geochemical analyses such as inductively coupled plasma mass spectrometry (ICP-MS), scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS), and X-ray diffraction (XRD) have improved source apportionment and compositional understanding, yet they often lack real-time detection and high-resolution spatiotemporal coverage. Emerging artificial intelligence (AI) tools, particularly the You Only Look Once (YOLO) deep learning framework, offer transformative opportunities for atmospheric dust monitoring by enabling rapid, automated plume detection across multispectral and hyperspectral datasets. This review demonstrates that ICP-MS, SEM-EDS, and XRD, when applied in combination, provide robust multi-dimensional source fingerprinting: ICP-MS isotopic ratios discriminate crystal from anthropogenic contributions, SEM-EDS resolves particle-level morphology and elemental composition, and XRD quantifies mineralogical assemblages that vary systematically with source region and transport pathway. Concurrently, successive YOLO generations (YOLOv5 through YOLOv10) have achieved real-time dust plume detection with mAP values exceeding 88% on satellite and UAV imagery. The proposed multimodal YOLO-geochemical integration framework, in which YOLO-guided plume detection triggers targeted field sampling and geochemical labels iteratively retrain detection models, enables compositionally resolved, real-time exposure mapping that directly supports inhalation risk assessment against WHO PM2.5 and PM10 thresholds and metal-specific reference concentrations. Collectively, these findings establish a scalable, evidence-based monitoring architecture that strengthens early-warning systems, informs air quality regulation, and advances global strategies to mitigate the environmental and public health burdens of dust storms.
7 June 2026
Read appraisal →BMJ paediatrics open
Impact of flash glucose monitoring versus capillary blood glucose monitoring on glycaemia in Indian youth with type 1 diabetes: a randomised crossover study
BACKGROUND: Data relating to flash glucose monitoring (FGM) use in low-resource settings are limited. Our study investigated the impact of FGM versus self-monitoring of blood glucose (SMBG) on glycaemia in Ahmedabad, India. METHODS: A randomised crossover study of FGM versus SMBG was undertaken. Participants aged 10-25 years (type 1 diabetes (T1D)>1 year) were randomised 1:1 to either Freestyle Libre 1 FGM use (intervention) for 6 months, followed by SMBG≥4 times/day (local care standard) for 6 months; or SMBG≥4 times/day, followed by FGM. After 12 months, everyone entered a 6-month observation period using the monitoring method choice. Insulin and dietary adjustments were undertaken as per local care standards. Glycated haemoglobin (HbA1c) was measured at 0, 3 and 6 months (period 1) and 9 and 12 months (period 2). Analyses included use of linear mixed-effects analysis of covariance, a paired Wilcoxon signed-rank test, and cumulative link mixed tests and model. RESULTS: Of 106 participants, 91 (86%) completed 12 months follow-up (47.3% female). At baseline, mean±SD age was 17.8±3.8 years, diabetes duration 9.9±5.0 years and HbA1c 8.6±1.9% (70±21 mmol/mol).HbA1c decreased when using FGM versus SMBG (difference -0.44% (4.8 mmol/mol); p=0.006), with greater reduction in those with higher baseline HbA1c (p=0.003). In the FGM→SMBG group, HbA1c initially decreased from 8.6±2.2% (70±24 mmol/mol) to 7.9±1.1% (62±12 mmol/mol) at 3 and 6 months (both p<0.05). After SMBG crossover, HbA1c was unchanged (7.9±1.1% (63±12 mmol/mol) at 9 months and 8.1±1.3% (65±14 mmol/mol) at 12 months). In the SMBG→FGM group, HbA1c was initially stable (8.6±1.4% (70±15 mmol/mol) at baseline; 8.8±1.7% (73±19 mmol/mol) at 6 months), but decreased after crossover to FGM (8.4±1.4% (68±15 mmol/mol) at 9 months; 8.3±0.9% (67±10 mmol/mol) at 12 months; p=0.023). CONCLUSION: This study provides evidence of improvement in glycaemic outcomes while using FGM in youth living with T1D in India. TRIAL REGISTRATION NUMBER: Clinical Trial Registry of India (CTRI/2022/02/020175).
1 June 2026
Read appraisal →Human vaccines & immunotherapeutics
Safety and durability of influenza and SARS-CoV-2 antibody responses through 6 months after a single dose of mRNA-1083, a multicomponent influenza and COVID-19 vaccine, in adults ≥50 years.
Seasonal influenza and SARS-CoV-2 continue to contribute substantially to global morbidity and mortality. mRNA-1083 is an investigational multicomponent mRNA vaccine targeting seasonal influenza and SARS-CoV-2. In this phase 3, observer-blind, active-controlled trial (NCT06097273), adults (aged ≥50 y) were randomly assigned (1:1) to receive mRNA-1083 (40 µg; plus placebo) or age-appropriate licensed comparator vaccines for influenza and COVID-19. Two substudies were included: Cohort A (≥65 y) and Cohort B (50-64 y). Primary objectives were to demonstrate noninferiority of mRNA-1083 versus comparators for influenza hemagglutination inhibition (HAI) responses and SARS-CoV-2 neutralizing antibody (nAb; PsVNA) responses at Day 29 after vaccination and to evaluate safety and reactogenicity of study vaccines. Here, we report safety, reactogenicity, and immunogenicity of mRNA-1083 through Day 181 in adults aged ≥50 y. mRNA-1083 induced HAI titers against all vaccine-matched influenza strains that were maintained through 6 months and were generally comparable to, or higher than, comparator responses. SARS-CoV-2 nAb responses remained higher for mRNA-1083 than comparators through 6 months. Reactogenicity was predominantly grade 1-2 in severity, and vaccination-related unsolicited adverse events were similar between groups. No serious adverse events or deaths related to vaccination were reported through 6 months. In adults aged ≥50 y, mRNA-1083 elicited durable influenza and SARS-CoV-2 humoral immune responses with an acceptable safety profile through 6 months. These findings support the use of mRNA-1083 as a multicomponent vaccine.ClinicalTrials.gov identifier: NCT06097273 (https://clinicaltrials.gov/study/NCT06097273).
1 June 2026
Read appraisal →JMIR research protocols
Creation of an mHealth Infrastructure to Support the Development and Delivery of mHealth Interventions: Protocol for Demonstration Projects Addressing Smoking Cessation in Cancer Care
BACKGROUND: Cancer remains a leading cause of morbidity worldwide. To reduce this burden, scalable, effective approaches are needed to address modifiable risk factors for cancer and support behavioral self-management. With smartphone ownership now nearly ubiquitous, mobile health (mHealth) interventions offer a powerful means to extend the reach, accessibility, and sustainability of evidence-based treatments for a variety of modifiable risk factors (eg, excessive alcohol use, physical inactivity, poor diet, and smoking). Moreover, the flexibility of mHealth platforms enables efficient delivery of novel interventions, supports innovative study designs, and facilitates real-time data collection to advance public health research. OBJECTIVE: Despite the great potential of mHealth interventions, developing high-quality mHealth tools is complex, time-consuming, and resource-intensive. To address these challenges, we are developing a coordinated, accessible, research-grade infrastructure for mHealth app development, testing, and dissemination. METHODS: The mHealth Florida infrastructure (mFLi) will provide a comprehensive, low-code software platform that enables researchers to build apps compatible with major mobile operating systems, namely, Apple iOS and Google Android. Through a modular interface, users will select from a menu of prebuilt features to tailor functionality to specific study needs. The platform will include 3 integrated environments (development, testing, and production), allowing researchers to prototype, evaluate, and deploy mHealth interventions. This infrastructure will be developed and maintained by a multidisciplinary team, ensuring that the platform is technically robust and usable and adheres to institutional and regulatory standards. To demonstrate the platform's functionality, utility, and adaptability, a multisite study comprising three initial projects focused on smoking cessation among patients with cancer is being conducted: (1) participant screening and enrollment, (2) randomization and treatment delivery, and (3) data processing using machine learning methods with on-device and cloud-based approaches. RESULTS: This study was funded in May 2023, and ethics approval was obtained from all involved sites' institutional review boards between February 2024 and October 2025. Recruitment began in March 2025 and enrollment is ongoing. As of January 2026, 41% (37/90) of the target sample have been enrolled and 21% (19/90) have completed their 6-month assessment. Data collection will be completed once the final participant completes their 6-month assessment (expected May 2027), with analyses commencing thereafter. Study findings are anticipated to be published in a peer-reviewed journal in 2027. CONCLUSIONS: Collectively, these projects will illustrate how mFLi can streamline app development, facilitate rapid translation of research into practice, and reduce barriers for researchers and developers. Ultimately, mFLi is designed to accelerate innovation in mHealth research, enhance access to behavioral interventions, and improve health outcomes among diverse populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT06909357; https://clinicaltrials.gov/study/NCT06909357. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/92288.
1 June 2026
Read appraisal →PloS one
Towards intelligent railway monitoring: A novel hybrid deep learning architecture for railway obstacle detection.
Railways are among the most efficient modes of transportation, capable of moving large quantities of goods and passengers over long distances at relatively low cost. However, accidents frequently occur due to objects or individuals present on the tracks, as trains are unable to swerve and require long braking distances. While the localization of objects within the track bed is a well-explored topic, the reliable and high-performance classification of such obstacles across all relevant categories remains an unresolved challenge. This study proposes an innovative hybrid architecture that leverages the specific visual characteristics of track bed imagery, setting a new benchmark in this domain. The hybrid design effectively leverages the strengths of ResNet50 and Swin Transformer V2, allowing the model to capture both local and global features. In addition, an Efficient Attention Module is integrated to further emphasize the most relevant features for robust obstacle classification. Using stratified five-fold cross-validation on a dataset of 2,003 images across six classes (iron bar, boulder, person, branch, canister, and barrel), the model achieved an average balanced accuracy of 99.46%. The results have implications for accident prevention, improving operational efficiency, and modernizing railway safety systems, thereby enabling the future application of automatic railway surveillance systems to ultimately enhance operational security.
1 June 2026
Read appraisal →African journal of reproductive health
How school-community cultural norms shape young people's reproductive health behaviors: Evidence from educational and behavioral research in China
This study systematically examines how school-community cultural norms shape young people's reproductive health behaviors in China. Using the PRISMA 2020 framework, a systematic review of empirical studies published between 2010 and 2022 was conducted to synthesize evidence from educational and behavioral research. Multiple international and Chinese databases were searched to identify qualitative, quantitative, and mixed-methods studies examining the influence of cultural norms within school and community settings on youth reproductive health knowledge, attitudes, and behaviors. Thematic synthesis, guided by the Social Ecological Model, was employed to integrate findings across studies. The review reveals that school-community cultural norms-particularly norms of silence, stigma, and gendered expectations-play a critical role in shaping reproductive health behaviors and in moderating the effectiveness of school-based interventions. Schools function both as reinforcers of prevailing community norms and as potential agents of change when culturally sensitive education is implemented. The findings underscore the need for context-specific, community-engaged reproductive health interventions tailored to the Chinese socio-cultural environment. Cette étude explore la relation complexe entre les normes culturelles et les comportements en matière de santé reproductive chez les jeunes en Chine, en se concentrant sur l'impact des environnements culturels école-communauté dans la formation de ces comportements. Elle examine comment les valeurs traditionnelles et les attentes sociales influencent les attitudes, les décisions et les actions des jeunes liées à la santé reproductive. En utilisant une approche de recherche qualitative, l'étude s'appuie sur des données secondaires à travers une revue approfondie de la littérature existante et de recherches antérieures, employant l'analyse de contenu pour extraire des insights détaillés. Les résultats soulignent que les normes culturelles école-communauté façonnent significativement les comportements en matière de santé reproductive, imposant souvent des effets restrictifs, les valeurs traditionnelles influençant profondément les décisions et les résultats de santé. L'étude met en lumière le besoin urgent d'interventions culturellement sensibles et spécifiques au contexte, conçues pour les jeunes Chinois. Elle souligne que les solutions efficaces doivent considérer l'interaction nuancée entre les normes culturelles, les contextes éducatifs et les pratiques de santé. En définitive, la recherche appelle à des programmes sur mesure capables de traiter ces complexités afin d'améliorer le soutien et les résultats en santé reproductive pour les jeunes en Chine.
31 May 2026
Read appraisal →Medicine
Machine learning identifies traffic-related pollutant mixtures as potential factors suggestive of association with osteoporosis in a cross-sectional analysis of NHANES
The combined effect of traffic-related pollutant mixtures on osteoporosis (OP) remains unclear. This study aimed to evaluate such associations using machine learning and mixture modeling approaches. A cross-sectional analysis was conducted among 3053 participants from the National Health and Nutrition Examination Survey 2015 to 2018. Eighteen exposures were assessed, including heavy metals, polycyclic aromatic hydrocarbons, phthalates, per- and polyfluoroalkyl substances, volatile organic compounds, diesel exhaust, and behavioral factors. OP was defined by femoral neck bone mineral density T-score ≤-2.5. Weighted quantile sum regression and 5 machine learning models were applied, accounting for complex survey design. OP prevalence was 12.97%. Weighted quantile sum regression showed a positive but nonsignificant mixture odds ratio (odds ratio = 1.21; 95% confidence interval: 0.77-2.63; P = .412). The largest positive weights were daily outdoor work duration (0.240) and occupational diesel exhaust (0.136). Random forest identified female sex, age, vitamin D, blood lead, and body mass index as top predictors. Least Absolute Shrinkage and Selection Operator achieved the highest test area under the receiver operating characteristic curve (0.81) with the lowest cross-validation standard deviation (0.0167). Its coefficients highlighted occupational diesel exhaust (β = 0.40) as a notable environmental factor alongside female sex (β = 0.95) and age (β = 0.70). Traffic-related pollutant mixtures showed a cross-sectional association with OP in a nationally representative US population, with occupational diesel exhaust and prolonged outdoor work emerging as key contributors in mixture models. However, the nonsignificant overall mixture effect and potential for reverse causation warrant caution in interpretation. These findings support considering environmental and occupational factors in OP prevention, although the overall mixture effect did not reach statistical significance.
31 May 2026
Read appraisal →Medicine
Predicting depressive symptoms in older adults with hearing impairment development and validation of NHANES-based machine-learning models: A cross-sectional study
Depressive symptoms frequently co-occur with hearing impairment in older adults, yet available prediction tools for this high-risk subgroup remain limited in practicality and applicability. We developed and internally validated prediction models for clinically relevant depressive symptoms among older adults with hearing impairment. We analyzed cross-sectional data from 5 National Health and Nutrition Examination Survey cycles (2005-2006, 2009-2010, 2011-2012, 2015-2016, and 2017-2018). Adults aged ≥60 years with hearing impairment were identified using the 2021 World Health Organization criterion (better-ear pure-tone average at 0.5/1/2/4 kHz ≥20 dB). Depressive symptoms were defined as a Patient Health Questionnaire-9 score ≥10. Candidate predictors included sociodemographic factors, comorbidities, lifestyle behaviors, and sensory/functional limitations; missing covariates were handled using multiple imputation. Participants were randomly split into training and validation sets (7:3). Predictors were selected using the Boruta algorithm followed by least absolute shrinkage and selection operator regression, yielding 6 predictors (age, poverty-income ratio, self-rated health, sleep disorder, memory difficulty, and physical functional limitation). Logistic regression and 6 machine-learning algorithms were developed. Model performance was assessed by discrimination (area under the receiver operating characteristic curve [AUC]), calibration (calibration curves and Brier score), and clinical utility (decision-curve analysis). The analytic sample included 2123 participants, of whom 154 (7.25%) had depressive symptoms. In the validation set, AUCs across models ranged from 0.799 to 0.862. Logistic regression achieved the highest discrimination (AUC 0.862, 95% CI 0.800-0.911) with good calibration (Brier score 0.053) and favorable net benefit across clinically relevant thresholds. A nomogram, a dynamic nomogram, and an online calculator were developed to facilitate individualized risk estimation. Sensitivity analyses showed broadly consistent results, except for attenuated discrimination in the severe hearing-loss subgroup. A parsimonious 6-variable model demonstrated strong discrimination, good calibration, and potential clinical utility for risk stratification and targeted screening among older adults with hearing impairment. External validation and prospective evaluation are warranted before clinical implementation.
31 May 2026
Read appraisal →JMIR research protocols
The Effectiveness of Art Activities and Peer Group Participation on Psychological Well-Being Among Older Adult Center Residents: Protocol for a Randomized Controlled Trial
BACKGROUND: Transitioning to residential centers often induces significant psychological stress in older adults, adversely affecting their psychological well-being (PWB) and ability to age healthily. Chinese art activities and their combination with peer group participation have demonstrated efficacy in improving emotional well-being and fostering social connectivity among younger populations but have not been examined in older adult populations to date. OBJECTIVE: This study aims to assess the efficacy of Chinese art activities or their combination with peer group participation in enhancing PWB among Chinese older adults living in a residential center. METHODS: This multicenter randomized, assessor- and analyst-blinded trial uses a "max-min-con" design with 3 groups: control, Chinese art activities, and Chinese art activities plus peer group participation (1:1:1 allocation). A total of 90 participants aged 60 to 85 years and with a stay of 1 year or less will be recruited from 3 older adult centers (30 from each center) and assigned via minimized randomization to the groups. Interventions will consist of 3 sessions within a single week (Monday, Wednesday, and Friday). Baseline evaluations will be conducted before randomization to assess PWB, loneliness, happiness, relaxation, and salivary cortisol levels. Outcome evaluations will be conducted 30 minutes prior to and following each intervention session to assess immediate effects. A follow-up evaluation is planned 1 week after the final intervention to measure sustained outcomes. RESULTS: The study was funded in September 2024. Participant recruitment commenced on May 9, 2025, and ended on August 20, 2025, with the recruitment of 90 participants. Data collection ended on October 31, 2025, and data analysis is expected to conclude in April 2026, with the anticipated publication of results in 2026. CONCLUSIONS: This study is the first randomized controlled trial to evaluate the effects of Chinese art activities, either alone or combined with peer group participation, on enhancing PWB in older people and the efficacy of salivary cortisol as a biomarker for the assessment of PWB. The findings will provide empirical evidence to assist policymakers and older adult centers in selecting appropriate interventions, with the long-term potential to improve psychological health in older adults.
31 May 2026
Read appraisal →Medicine
Machine learning-based identification of multidimensional predictors of quality of life in individuals with multiple sclerosis
This study aimed to identify independent predictors of quality of life in patients with multiple sclerosis (MS) using machine learning approaches. One hundred and one individuals diagnosed with MS were included in this cross-sectional study. Quality of life was assessed using the MS Quality of Life-54 (MSQoL-54). Demographic variables, clinical characteristics, disability level (Expanded Disability Status Scale [EDSS]), fatigue severity, sleep quality (Pittsburgh Sleep Quality Index), depression level (Beck Depression Inventory), and functional mobility (Timed Up and Go test) were evaluated. Multiple machine learning regression models, including Linear Regression, Lasso, Elastic Net, Support Vector Machines, Random Forest, and XGBoost, were developed and compared. Five-times repeated five-fold cross-validation was applied for internal validation. Model performance was evaluated using root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). Among all models, Lasso regression demonstrated the best predictive performance (RMSE = 5.02, MAE = 4.04, R2 = 0.86). Disability level (EDSS) emerged as the strongest negative predictor of quality of life, followed by fatigue severity, sleep quality, and impaired functional mobility. Although disease duration was not significantly correlated with quality of life in univariate analyses, it showed a positive contribution in the multivariable model. Depression showed a strong bivariate association but had a relatively lower weight in the final predictive model. Quality of life in individuals with MS is strongly influenced by disability, fatigue, sleep quality, and functional mobility. Machine learning approaches provide an effective and interpretable framework for identifying key determinants of quality of life and may support personalized rehabilitation and clinical decision-making in MS.
31 May 2026
Read appraisal →African journal of reproductive health
The role of information technology in promoting sexual and reproductive health awareness among young people in Lahore: A comparative study with Shanghai.
Information technology (IT) has transformed access to health information, yet its impact on sexual and reproductive health (SRH) awareness varies across contexts. This study investigates IT's influence on youth SRH awareness in Lahore, Pakistan, using primary data, and provides a comparative analysis with secondary data from Shanghai, China. Using a cross-sectional design in Lahore (n=250), structured questionnaires, PLS-SEM, logistic regression, and ANOVA assessed relationships between IT use, digital health literacy, trust in digital sources, cultural barriers, and awareness outcomes. Results indicate IT use (β=0.42), digital health literacy (β=0.38), and trust (β=0.26) significantly enhance awareness in Lahore, while cultural barriers exert a strong negative influence (β=-0.31). Significant mean differences (p<0.001) were found between cities. Shanghai demonstrated higher digital literacy, trust, awareness, and use of structured platforms, while Lahore exhibited substantially higher cultural barriers. Model comparisons showed stronger predictive pathways in Shanghai (R²=0.74) than Lahore (R²=0.68), reflecting advantages of institutionalized sex education and government-certified digital health applications. Overall, while IT holds considerable potential, its effectiveness is shaped by cultural norms, digital infrastructure, and institutional trust. The findings underscore Pakistan's need to develop culturally appropriate, reliable, and institutionally supported digital health platforms to improve youth access to accurate SRH information. La technologie de l'information (TI) a transformé l'accès à l'information sanitaire, mais son impact sur la sensibilisation à la santé sexuelle et reproductive (SSR) varie selon les contextes. Cette étude examine l'influence des TI sur la sensibilisation des jeunes à la SSR à Lahore, au Pakistan, avec une analyse comparative de Shanghai, en Chine. En utilisant un design transversal à Lahore (n=250), des questionnaires structurés, la PLS-SEM, la régression logistique et l'ANOVA ont évalué les relations entre l'utilisation des TI, la littératie numérique en santé, la confiance dans les sources numériques, les barrières culturelles et les résultats de sensibilisation. Les résultats indiquent que l'utilisation des TI (β=0,42), la littératie numérique en santé (β=0,38) et la confiance (β=0,26) améliorent significativement la sensibilisation à Lahore, tandis que les barrières culturelles exercent une forte influence négative (β=-0,31). Des différences moyennes significatives (p<0,001) ont été constatées entre les villes. Shanghai a démontré une littératie numérique, une confiance, une sensibilisation et une utilisation de plateformes structurées plus élevées, tandis que Lahore présentait des barrières culturelles substantiellement plus fortes. Les comparaisons de modèles ont montré des voies prédictives plus solides à Shanghai (R²=0,74) qu'à Lahore (R²=0,68), reflétant les avantages de l'éducation sexuelle institutionnalisée et des applications de santé numériques certifiées par le gouvernement. Globalement, bien que les TI aient un potentiel considérable, leur efficacité est façonnée par les normes culturelles, l'infrastructure numérique et la confiance institutionnelle. Les conclusions soulignent la nécessité pour le Pakistan de développer des plateformes de santé numériques culturellement adaptées, fiables et soutenues institutionnellement pour améliorer l'accès des jeunes à des informations précises sur la SSR.
31 May 2026
Read appraisal →BMJ open
Multicentre randomised controlled trial of the Norwegian health in work service for patients with common mental disorders or musculoskeletal disorders: the Norwegian Sickness Absence Clinic (NSAC) Efficacy Study
INTRODUCTION: In many countries, a high or increasing rate of sickness absence is challenging the sustainability of present sickness absence benefit schemes. Most sickness absence is certified on the grounds of common mental disorders or musculoskeletal disorders, and substantial effort has been invested in developing interventions promoting return to work for these patients. In Norway, the Health in Work ((HelseIArbeid), HIA) clinics were established as outpatients' services within the specialised healthcare system, with the aim of improving health and supporting return to work. The HIA service admits patients with low-to-moderate anxiety/depression and/or musculoskeletal disorders. In this protocol, we describe the naturalistic multicentre randomised controlled trial Norwegian Sickness Absence Clinic Efficacy study, which aims to determine the effect of HIA on work participation and health. METHODS AND ANALYSES: The HIA outpatient service is staffed by clinical psychologists, physiotherapists, medical specialists in physical medicine and rehabilitation and employment support supervisors from the Norwegian Labour and Welfare Administration. Patients admitted to HIA have access to multidisciplinary assessment and treatment. The trial recruits' patients from five HIA outpatient clinics in Northern Norway. Patients are randomised in equal proportions to either (1) rapid HIA (assessment within 4 weeks), (2) delayed HIA (assessment within 10-14 weeks) or (3) active control, which consists of a monodisciplinary examination at HIA close to diagnosis-specific deadline for examination as suggested by guidelines (8-26 weeks). The trial commenced recruitment on 16 January 2023 and will recruit 2500 patients. The aim is to assess the effect of the HIA service, with the hypothesis that the HIA concept is superior to what resembles treatment as usual, in improving employment and preventing long-term welfare dependency. Secondary outcomes include self-reported symptoms of health problems. We also examine the effect the service has on other healthcare utilisation. To date, no research has been conducted to assess the efficacy of the HIA service. If proven efficacious, and if there is an economic case for this investment in tailored healthcare delivery, the policy implication may be implementation of the service at scale. If not, adaptations or investments into other viable paths of treatment may be considered. ETHICS AND DISSEMINATION: The study is approved by the Regional Committee for Medical Research Ethics (REC North, #122770). Results from the study will be disseminated at national and international scientific conferences, to funders and participating outpatient clinics in seminars and in peer-reviewed scientific journals. TRIAL REGISTRATION NUMBER: NCT05310695.
31 May 2026
Read appraisal →BMJ open
Patterns and determinants of primary care virtual health service use among rural Aboriginal and Torres Strait Islander adults with chronic diseases: a cross-sectional study
OBJECTIVE: To examine virtual health service (VHS) device usage patterns and identify factors associated with VHS engagement among Indigenous Australian adults with chronic conditions. DESIGN: Cross-sectional survey. SETTING: An Aboriginal Community Controlled Health Organisation providing primary healthcare services across rural and remote Queensland, Australia. PARTICIPANTS: 74 consenting Indigenous Australian adults with at least one chronic condition who were registered VHS users. METHODS: Participants completed surveys assessing their use of four Bluetooth-enabled monitoring devices (pulse oximeter, blood glucose monitor, blood pressure monitor, weight scale) over a 2-week recall period. The primary outcome was VHS device usage status, categorised as active versus inactive users. Active users were defined as participants who reported any frequency of device use, while those reporting no use were classified as inactive users. All participants had access to Indigenous health coach support as part of the VHS model. Binary logistic regression was used to identify sociodemographic and geographical factors associated with VHS engagement. RESULTS: Sixty-four per cent (n=47) were active users, with 73% of these using all four devices concurrently. Among active users, blood pressure monitors showed the highest utilisation (98%), followed by weight scales (91%), blood glucose monitors (89%) and pulse oximeters (86%). Three factors were significantly associated with VHS usage using binary logistic regression: residing in medium rural towns (adjusted OR 4.71, 95% CI 1.23 to 17.94, p=0.02), age 18-65 years (adjusted OR 3.59, 95% CI 1.05 to 12.22, p=0.04) and having multiple chronic conditions (adjusted OR 10.95, 95% CI 1.25 to 95.87, p=0.03) compared with those in more remote areas, aged ≥66 years and with single condition, respectively. CONCLUSION: Indigenous-led VHS achieve substantial engagement through culturally grounded health coach support. However, addressing digital connectivity in remote areas, age-appropriate support for older adults and Indigenous workforce development is essential to ensure equitable access and sustained engagement.
31 May 2026
Read appraisal →JMIR infodemiology
Early Depression Detection in Social Media: Monitoring of Individual Nighttime Dynamics and Large Language Model Analysis
BACKGROUND: Depression has become a major global public health challenge, and early intervention is critical for improving patient outcomes. Current depression detection techniques based on social media data (traditional risk detection) rely heavily on users' complete historical information, which cannot meet the timeliness requirements of early intervention. This underscores the need for early risk detection (ERD) methods emphasizing early-stage, real-time warning. However, existing ERD studies have notable limitations such as (1) they overlook temporal activity patterns hidden in posting time stamps, missing vital warning signals; and (2) they depend on static templates or resource-intensive sequence models, resulting in limited interpretability and inefficient use of early data, ultimately constraining their clinical applicability for early intervention. OBJECTIVE: This study aims to develop an efficient, reliable, and interpretable ERD model. The core objectives are to extract temporal activity patterns features from posting time stamps, thereby enriching feature dimensions for risk detection; to leverage large language models (LLMs) for improved text filtering precision and depression-related factor analysis; and to achieve accurate early detection of depression to support clinical intervention. METHODS: We propose the Monitoring of Individual Nighttime Dynamics (MIND) and LLM analysis model, which integrates two key innovations: (1) circadian activity dynamics: posting time stamps are transformed into temporal activity patterns, analyzing fluctuations in posting frequency and timing to derive sleep-related features, thereby compensating for the limitations of text-only approaches, and (2) LLM depression profiler: LLMs are used for dynamic text filtering, automatically removing irrelevant noise and focusing on potential depression-related cues. Based on LLM semantic understanding, latent depression risk factors are identified, enhancing interpretability for clinical treatment and robustness to noise. RESULTS: Experiments on the eRisk2017 (data source: Reddit [Reddit Inc]) benchmark dataset demonstrated that MIND significantly outperformed existing baseline models in early detection sensitivity, specificity, and accuracy. By combining sleep-related features with text analysis, the model achieved interpretable, traceable predictions that can support clinical treatment. ALL relevant experimental code is publicly available. CONCLUSIONS: The MIND model combines temporal activity pattern features with LLM-based text analysis, addressing the challenges of poor interpretability and inefficient use of early-stage data in existing ERD methods. It significantly enhances early detection performance, offering a new paradigm for applying social media data in ERD, thereby enabling earlier intervention and reducing the public health burden of depression.
31 May 2026
Read appraisal →Human vaccines & immunotherapeutics
Strategies implemented to increase HPV vaccine uptake and confidence among men who have sex with men and transgender people: A systematic review
Men who have sex with men (MSM) and transgender persons are disproportionately affected by HPV-related disease. The HPV vaccine effectively prevents infection, but vaccine uptake remains suboptimal in this group. Thus, this systematic review aimed to synthesize the literature on interventions and strategies implemented to increase HPV vaccine confidence and uptake among MSM and transgender persons. Six databases were searched in May 2025. We assessed risk of bias and extracted and descriptively summarized key data through narrative synthesis and content analysis. Sixteen articles reporting on eight interventions were identified, all implemented in high-income settings. The interventions can be broadly categorized into two types: strategies to integrate HPV vaccination into existing health services and digital interventions aimed at generating vaccine demand. Overall, evidence remains limited on interventions to increase HPV vaccine uptake in these groups, particularly studies focusing on the needs of transgender persons.
31 May 2026
Read appraisal →Medicine
Burden of Helicobacter pylori infection in children and adults in Vietnam: A systematic review and meta-analysis of prevalence
BACKGROUND: Although Helicobacter pylori (H. pylori) prevalence has declined in many high-income countries, data from Vietnam remain limited and fragmented. This systematic review and meta-analysis aimed to estimate the pooled prevalence of H. pylori infection in Vietnamese adults and children. METHODS: A systematic search of PubMed, Embase, Scopus, and Web of Science was conducted for observational studies published between January 2000 and September 2025. Eligible studies reported H. pylori prevalence in Vietnamese populations using validated diagnostic methods. Random-effects meta-analyses were used to calculate pooled prevalence estimates with 95% confidence intervals (CIs). Subgroup analyses were conducted by age group, geographic area, and study setting. RESULTS: Twenty-five studies met inclusion criteria, comprising 8204 adults and 4641 children. The pooled prevalence of H. pylori infection was 58.7% (95% CI: 49.9%-67.2%) in adults and 77.2% (95% CI: 67.1%-86.0%) in children, with high heterogeneity across studies (I2 > 98%, P < .001). Among adults, prevalence was 56.4% in those aged <50 years and 65.8% in those ≥50 years (P = .455). Prevalence was lower in rural areas (46.8%) compared to urban areas (60.7%) (P = .045), with no significant difference between community- and hospital-based settings (P = .723). Funnel plot assessment did not indicate evident publication bias. CONCLUSION: H. pylori infection remains common in the populations represented in this study, particularly among urban and healthcare-seeking groups in Vietnam. These findings underscore the need for expanded surveillance and monitoring to better characterize H. pylori infection patterns and inform appropriate response strategies.
31 May 2026
Read appraisal →PloS one
Effect of digitizing Community Health Information System on the delivery and use of maternal and child health services: Propensity score matching analysis
INTRODUCTION: In 2018, Ethiopia's government digitized its Community Health Information System (eCHIS) to enhance Health Extension Program service delivery. However, the impact of eCHIS on health outcomes remains unclear. This study, therefore, examined the effects of eCHIS on the uptake of maternal and child health services. METHODS: A post-test-only, non-equivalent group household survey design was used, collecting data from July to August 2024 in rural communities with and without eCHIS. A stratified multistage sampling technique was employed to recruit respondents. A sample of 1,728 women of reproductive age (271 in eCHIS and 1,457 in non-eCHIS woredas), 1,118 women with children ages 0-11 months (188 in eCHIS and 930 in non-eCHIS), and 569 women with children ages 12-23 months (301 in eCHIS and 268 in non-eCHIS) were included in this study. Propensity scores were used to match intervention and comparison communities based on women's age, religion, parity, education, household wealth, distance to health facilities, and autonomy. A modified Poisson regression analysis, adjusting for covariates, was conducted to estimate the adjusted prevalence ratios (PR) for maternal and child health outcomes. RESULTS: Modern contraceptive use was 66% in intervention areas versus 56% in comparison areas. Institutional delivery rates were 95% in intervention and 79% in comparison areas. In intervention areas, 94% of children received the first dose of the Pentavalent vaccine compared to 83% in comparison areas, while 85% and 68%, respectively, received the third dose. Adjusted analyses showed that eCHIS intervention areas had statistically significant increases in contraceptive use (13.0 percentage points; PR: 1.25; p-value < 0.01) and institutional deliveries (8.9 percentage points; PR: 1.18; p-value < 0.01) compared to comparison areas. Similarly, the average treatment effect of eCHIS on Pentavalent 1, Pentavalent 3, and full vaccination coverage showed significant increases of 10.3 (PR: 1.13; p-value < 0.01), 13.6 (PR: 1.26; p-value < 0.01), and 14.6 (PR: 1.36; p-value < 0.01) percentage points, respectively. CONCLUSION: This study underscores the transformative potential of eCHIS in improving maternal and child health outcomes in Ethiopia. Sustained investment in digital health systems can help scale effective health care services to rural and underserved communities.
31 May 2026
Read appraisal →Medicine
Prevalence and long-term outcomes of brain fog and cognitive impairment in individuals with long COVID: A systematic review
BACKGROUND: Long COVID is increasingly recognized as a complex multisystem condition, with brain fog and cognitive impairment emerging as some of its manifestations. Despite growing literature, the pooled prevalence, subgroup differences, and underlying mechanisms remain incompletely understood. METHODS: We systematically reviewed 47 studies (2000-2025) encompassing over 25,000 patients to evaluate the prevalence of brain fog and cognitive impairment among long COVID populations. Data were extracted on study design, patient demographics, follow-up duration, and subgroup variables including gender, hospitalization, vaccination, and geographic region. Risk of bias was assessed using the Newcastle-Ottawa Scale (NOS v9.0) and JBI checklists. Quantitative synthesis was performed with subgroup and temporal analyses, presented in forest plots and summary figures. RESULTS: The pooled prevalence of brain fog was 30% (95% CI: 28-32), while cognitive impairment was 25% (95% CI: 23-27). Female patients consistently showed higher rates compared to males (34% vs 23% for brain fog; 29% vs 21% for cognitive impairment). Community-managed patients demonstrated higher prevalence compared to hospitalized cohorts, and unvaccinated individuals had a greater burden than vaccinated ones. Temporal analyses indicated that prevalence increased with longer follow-up, suggesting symptom persistence or late manifestation. Pathophysiological explanations include neuroinflammation, microvascular injury, immune dysregulation, and psychosocial stressors. CONCLUSION: Brain fog and cognitive impairment are common, persistent, and clinically significant features of long COVID. Gender differences, vaccination status, and follow-up duration influence prevalence. Future studies should focus on mechanisms, preventive strategies, and targeted interventions to mitigate long-term cognitive sequelae.
31 May 2026
Read appraisal →Scientific reports
Prevalence and Risk Factors for Cytomegalovirus Retinitis Among People Living with HIV in Sub-Saharan Africa in the Antiretroviral Therapy Era: A Systematic Review and Meta-Analysis
Cytomegalovirus retinitis has remained an alarming and potentially vision-threatening opportunistic disease in the population living with HIV, especially in cases of extreme immunosuppression. Although the introduction of antiretroviral therapy has led to a drastic decline in the number of cytomegalovirus retinitis cases reported in most parts of the world, the current epidemiology of cytomegalovirus retinitis in sub-Saharan Africa has seemed unusual in early reports, unexpectedly portraying low disease prevalence rates despite the high number of HIV cases in the concerned region. This systematic review and meta-analysis aimed to estimate the pooled prevalence of cytomegalovirus retinitis among people living with HIV in sub-Saharan Africa in the antiretroviral therapy era, and to identify associated risk factors. The search of databases included Medline using the search engine PubMed, Google Scholar, and the African Journals Online database named AJOL. For inclusion, studies must have included an eye examination to verify the presence of cytomegalovirus retinitis. The data was combined using the logit transformation model. Heterogeneity was tested using the I-squared test and the Cochran Q test. A total of ten studies involving 1,931 participants from nine sub-Saharan Africa countries were found eligible. The proportion of cytomegalovirus retinitis varied from 0.34% to 15.8%. Pooled prevalence was found to be 3% (95% CI: 1.6-5.4%) with low to moderate inter-study variation (I² = 17.8%). Substantial variation in the proportion was found in different sub-Saharan Africa regions; it was found to be less than 1% in West Africa, 3-4% in Southern Africa, 7% in East Africa and 6% in Central Africa. Across all studies, the strongest and most consistent risk factors for cytomegalovirus retinitis were profound immunosuppression, particularly CD4 < 50 cells/µL. Antiretroviral therapy-naïve status, poor adherence, and presence of advanced AIDS-defining illnesses were additional contextual risk markers. Cytomegalovirus retinitis is an under-recognized but important source of preventable blindness among people living with HIV. Prevalence in sub-Saharan Africa differed from that in Asian early antiretroviral therapy era cohorts but is relevant in settings where late HIV presentation occurs. Systematic retinal screening in people living with HIV with low CD4 counts < 50 cells/µL and expanded HIV care and treatment services are important to prevent blindness due to cytomegalovirus retinitis.
31 May 2026
Read appraisal →Journal of global health
Global, regional, and national trends in blindness and vision loss, 1990-2021: a secondary ecological trend analysis based on modelled population estimates.
BACKGROUND: We aimed to provide global, regional, and national estimates of the burden of blindness and vision loss from 1990 to 2021, stratified by cause, age, and sociodemographic index (SDI). METHODS: This population-based study used data from the 2021 Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD) study, covering 1990 to 2021. It evaluates the burden of blindness and vision loss based on prevalence, age-standardised prevalence rate (ASPR), disability-adjusted life years (DALYs), age-standardised DALY rate (ASR of DALY), and average annual percent changes (AAPCs). RESULTS: Globally, the ASPR of blindness and vision loss increased from 12 453.52 (95% uncertainty interval (UI) = 10 287.58, 15 226.09) in 1990 to 15 784.33 (95% UI = 12 761.44, 19 502.32) in 2021, with an AAPC of 0.85 (95% confidence interval (CI) = 0.7, 1.11, P < 0.001). In contrast, the ASR of DALYs remained stable, changing from 342.01 (95% UI = 237.87, 482.17) in 1990 to 342.78 (95% UI = 224.21, 503.61) in 2021, with an AAPC of 0.05 (95% CI = -0.04, 0.2, P = 0.298). Notably, near vision loss and cataract showed consistent increases, with AAPCs of 1.14 (95% CI = 0.94, 1.51, P < 0.001) and 0.25 (95% CI = 0.16, 0.33, P < 0.001), respectively. Blindness and vision loss prevalence was significantly higher in low and low-middle SDI regions compared to other SDI regions. CONCLUSIONS: Global blindness and vision loss increased from 1990 to 2021, while DALYs stayed stable. Prevention should be tailored by region, country, gender, cause, and age.
31 May 2026
Read appraisal →BMJ open
The association of the Healthy Lifestyle Index (HLI) and HLI trajectories with risk of all-cause and cause-specific mortality: a GRADE-assessed dose-response systematic review and meta-analysis.
BACKGROUND: The Healthy Lifestyle Index (HLI) integrates key behaviours to assess their cumulative impact on health. While higher HLI adherence is linked to lower disease and mortality risk, its long-term trajectory association remains understudied. This study aims to examine the dose-response relationship and long-term association of HLI on mortality risks. DESIGN: Systematic review and dose-response meta-analysis using the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) approach. DATA SOURCES: PubMed, Scopus and Web of Science were searched until June 2024. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included observational cohort studies that assessed the relationship of HLI or its trajectories with all-cause, cardiovascular disease (CVD)-cause or cancer-cause of mortality. RESULT: Analysis of 13.7 million participants demonstrated that higher adherence to the HLI is linked to lower risk of all-cause (HR: 0.48; 95% CI 0.46 to 0.53; GRADE: moderate), CVD-cause (HR: 0.49; 95% CI 0.44 to 0.51; GRADE: moderate) and cancer-cause mortality (HR: 0.55; 95% CI 0.49 to 0.61; GRADE: low). These associations were further confirmed in a dose-response manner. Moreover, compared with maintaining an unhealthy lifestyle, a decline in HLI adherence was associated with a 14% higher risk of all-cause and a 19% higher risk of cancer-related mortality. In contrast, an improvement in HLI adherence was linked to a 20% lower risk of all-cause and a 13% lower risk of cancer-related mortality. CONCLUSION: Adherence to HLI and its long-term patterns are associated with lower mortality risk. These findings emphasise the importance of lifestyle-based prevention and intervention strategies in reducing mortality. PROSPERO REGISTRATION NUMBER: CRD42024500538.
31 May 2026
Read appraisal →BMJ open
Birth outcomes for women with pre-existing mental health problems: a systematic review and meta-analysis
OBJECTIVES: To synthesise evidence on the association between any diagnosed or self-reported mental health problems prior to pregnancy (pre-existing mental health problems) and birth outcomes including preterm birth (PTB), low birth weight (LBW), small for gestational age (SGA), neonatal unit (NNU) admission and mode of birth (instrumental birth, planned or unplanned caesarean section). METHODS: Systematic searches were conducted in MEDLINE, CINAHL, Embase and PsycINFO in December 2024 for studies examining the association between any pre-existing mental health problems and PTB, LBW, SGA, NNU admission and mode of birth. Only articles published in English were included with no restriction on year of publication. Two reviewers independently screened studies and extracted data. Study quality was assessed using the Newcastle-Ottawa Scale and Joanna Briggs Institute checklists. Random-effects meta-analyses were conducted to pool crude and adjusted ORs (aORs) and risk ratios (aRR) with 95% CIs. ORs and RRs were analysed separately. Between-study heterogeneity was quantified using the I2 statistic. RESULTS: Of 15 467 records screened, 33 studies met the inclusion criteria. Women with any pre-existing mental health problems had higher odds and risks of adverse birth outcomes, including PTB (aOR 1.41, 95% CI 1.27 to 1.56) (aRR 1.36, 95% CI 1.21 to 1.51), LBW (aOR 1.28, 95% CI 1.22 to 1.33) (aRR 1.32, 95% CI 1.04 to 1.68), SGA (aOR 1.27, 95% CI 1.07 to 1.51) (aRR 1.34, 95% CI 1.19 to 1.51) and NNU admission (aOR 1.44, 95% CI 1.19 to 1.74). Adjusted estimates were based on multivariable models that commonly controlled for maternal age, parity and socio-demographic factors. No consistent associations were observed between pre-existing mental health problems and mode of birth. CONCLUSIONS: Pre-existing mental health problems were associated with increased risks and odds of several adverse birth outcomes. These findings highlight the importance of early identification and targeted support for women with mental health problems before pregnancy to strengthen preconception and maternity care planning. PROSPERO REGISTRATION NUMBER: CRD42023485834.
31 May 2026
Read appraisal →Journal of medical Internet research
Effects of Multicomponent Digital Health Interventions on Multidimensional Physical Activity in Older Adults: Systematic Review, Meta-Analysis, and Meta-Regression of Randomized Controlled Trials
BACKGROUND: The comprehensive effects of multicomponent digital health interventions (DHIs) on multidimensional physical activity indicators and sedentary behavior (SB) remain controversial. OBJECTIVE: This systematic review aimed to evaluate the impact of multicomponent DHIs on daily steps, moderate-to-vigorous physical activity (MVPA), light physical activity, total physical activity, and SB in older adults. METHODS: PubMed, Web of Science, Embase, The Cochrane Library, and CINAHL were searched up to February 20, 2026. Randomized controlled trials concerning multicomponent DHIs for promoting exercise behavior in older adults were included. RoB 2.0 was used to evaluate study quality. Meta-analyses were performed using the Hartung-Knapp-Sidik-Jonkman random-effects model, and 95% prediction intervals (PIs) were calculated via Nagashima adjustment to evaluate effect dispersion. The GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) system was used to evaluate evidence certainty. RESULTS: A total of 26 randomized controlled trials (n=4129) were included. The results showed that multicomponent DHIs significantly improved daily steps (mean difference [MD] 822.8, 95% CI 198.3 to 1447.3 steps/d; 95% PI -1452.4 to 3098.0) and MVPA (MD 45.9, 95% CI 23.9 to 67.9 min/wk; 95% PI -9.4 to 101.2). However, the improvements in SB (MD -283.7, 95% CI -610.8 to 43.5 min/wk; 95% PI -984.5 to 417.1), total physical activity (MD 104.4; 95% CI -109.2 to 318.0 min/wk; 95% PI -444.4 to 653.2), and light physical activity (MD 39.3, 95% CI -96.2 to 174.7 min/wk; 95% PI -227.6 to 306.2) did not reach statistical significance. As some included studies combined digital tools with human support, the independent contribution of digital technology remains uncertain. PIs indicated a certain degree of dispersion across different clinical contexts. Subgroup analysis showed higher effect sizes for standalone wearables, human-assisted interventions, and populations with chronic disease risks. Meta-regression showed that effect sizes remained stable across different ages and durations. The trim-and-fill method confirmed the robustness of MVPA results. GRADE assessment indicated "moderate" certainty for MVPA and "low" for daily steps and other indicators. CONCLUSIONS: This systematic review suggests that multicomponent DHIs may serve as an effective means for enhancing daily steps and MVPA in older adults. The innovation lies in evaluating the true effect distribution of multicomponent DHIs through Hartung-Knapp-Sidik-Jonkman random-effects models and Nagashima PIs. Compared with previous studies, this review identified the impact of population characteristics and control group differences on effect estimates using PI and subgroup models, confirming that advanced age did not significantly diminish the good adaptability of older adults to DHIs. Evidence limitations include high heterogeneity, lack of long-term follow-up, and differences between objective and subjective measurement tools. In practice, priority should be given to hardware carriers with simplified interaction and integrated human support, with tailored strategies developed for different risk subgroups.
30 May 2026
Read appraisal →PloS one
Burden and patterns of dyslipidaemia among adult Ghanaians: A systematic review
BACKGROUND: Dyslipidaemia is a major modifiable risk factor for cardiovascular disease and has become an increasing public health concern in sub-Saharan Africa. Rapid urbanisation, dietary transitions, and sedentary lifestyles have contributed to the rising incidence of cardiometabolic diseases in Ghana. However, evidence on the overall burden and patterns of dyslipidaemia in adults remains unclear. This systematic review aimed to synthesise the evidence on the prevalence and lipid profile patterns of adult Ghanaians. METHODS: A comprehensive search of PubMed, Scopus, Web of Science, African Journals Online, Africa-Wide Information and African Index Medicus databases was conducted for studies published between January 1980 and November 2025. Eligible studies reported the prevalence or distribution of dyslipidaemia in Ghanaian adults (≥ 18 years). Two reviewers independently screened, extracted, and assessed the quality of included studies. Findings were synthesised narratively and summarised in descriptive tables and figures, due to heterogeneity in study designs and data reporting. RESULTS: Twenty-four studies published between 2003 and 2023, comprising approximately 11,400 participants, met the inclusion criteria. Across the included studies, the reported prevalence of dyslipidaemia ranged from 3.0% to 72.4%, reflecting differences in study populations, diagnostic criteria and study settings. Low high-density lipoprotein cholesterol (HDL-C) was the most frequent abnormality, followed by elevated total and low-density lipoprotein cholesterol (LDL-C), whereas hypertriglyceridaemia was the least common. Studies from southern and middle regions-particularly Ashanti, Brong-Ahafo, and Greater Accra-reported a higher dyslipidaemia prevalence than those from northern Ghana. Considerable variation in diagnostic criteria, study populations and sampling strategies limited comparability and precluded meta-analysis. CONCLUSION: Dyslipidaemia is common among adult Ghanaians, with low HDL-C emerging as the predominant abnormality. Methodological differences and sampling biases limit the precise estimation of the national burden, but the available evidence indicates a growing cardiometabolic risk. Future studies should prioritise community-based sampling and context-appropriate lipid thresholds to support evidence-based cardiovascular risk-reduction strategies.
30 May 2026
Read appraisal →African journal of reproductive health
Artificial intelligence-enabled digital reproductive health education: corpus-based strategies for strengthening Spanish health communication capacity
This study examines how corpus-grounded artificial intelligence (AI) can strengthen Spanish reproductive health communication capacity within China's digital health ecosystem. A mixed-methods design was employed, combining corpus linguistics, AI-assisted message generation, expert-informed evaluation, and quantitative user assessment. A domain-specific Spanish reproductive health corpus was constructed from 3,052 documents, including clinical guidelines, patient education materials, and FAQs/user queries, yielding 1,065,110 tokens for linguistic analysis and AI grounding. Corpus-derived readability benchmarks, lexical simplification rules, and discourse patterns were integrated into an AI content generation pipeline to produce reproductive health messages, which were then compared with non-corpus-grounded AI outputs. The user evaluation phase was conducted among 240 Spanish-speaking or Spanish-proficient adults in selected Chinese metropolitan cities. Data were collected through a structured questionnaire measuring Corpus-Grounded AI Generation, Spanish Communication Quality, and Health Communication Capacity, and were analyzed using reliability testing, correlation analysis, and structural equation modeling. The findings showed that corpus-grounded AI significantly improved Spanish communication quality, while communication quality had the strongest effect on users' comprehension, confidence, and help-seeking intention. Mediation analysis further demonstrated that Spanish communication quality significantly mediated the relationship between corpus-grounded AI generation and health communication capacity. The study concludes that linguistically informed AI design can enhance the clarity, accessibility, and effectiveness of reproductive health education and offers a practical framework for multilingual digital health communication in sensitive healthcare contexts. Cette étude visait à examiner le rôle de l'IA guidée par la linguistique de corpus dans l'amélioration de la qualité de la communication en espagnol sur la santé reproductive au sein de l'écosystème numérique chinois. En utilisant une approche à méthodes mixtes, la recherche a combiné l'analyse de corpus de textes espagnols sur la santé reproductive, la génération de contenu basée sur l'IA et l'évaluation par les utilisateurs. Un corpus espagnol spécifique au domaine de la santé reproductive a été construit et intégré dans un pipeline de génération d'IA ancré dans le corpus pour optimiser la lisibilité, l'exactitude et la sensibilité culturelle. La qualité de la communication et la capacité de communication en santé ont été mesurées à l'aide d'une analyse de fiabilité, de tests de corrélation et de modélisation par équations structurelles. Les résultats ont révélé que l'IA ancrée dans le corpus améliore significativement la qualité de la communication en espagnol, ce qui améliore à son tour la compréhension des utilisateurs, l'auto-efficacité et les intentions de recherche d'aide. La qualité de la communication est apparue comme un mécanisme médiateur clé entre la conception de l'IA et les résultats en matière de communication santé. Sur le plan théorique, l'étude établit une base pour intégrer la linguistique de corpus dans les systèmes d'éducation à la santé pilotés par l'IA, tandis que sur le plan pratique, elle propose un cadre évolutif pour les plateformes multilingues d'éducation à la santé reproductive. Ces résultats ont des implications importantes pour les politiques mondiales de santé numérique, la gouvernance de l'IA et les stratégies de communication en santé reproductive.
30 May 2026
Read appraisal →BMJ global health
Systematic review and meta-analysis of interventions for mental health in extreme weather events
INTRODUCTION: Climate change leading to extreme weather events (EWEs) poses critical threat to human health, including mental well-being. As the effects of climate change are becoming more pronounced, there is a need to identify effective interventions to mitigate the mental health impacts. METHODS: The aim of this review was to synthesise the existing literature on interventions to prevent and manage mental health symptoms in people affected by EWEs. We conducted a comprehensive literature search in MEDLINE, EBSCO CINAHL and Cochrane till 7 February 2024 and in Web of Science and EMBASE till 20 February 2024. Randomised controlled trials (RCTs), quasi-experimental studies and before-after study designs were included. Our search yielded 11 083 potentially relevant papers, which were screened by titles and full texts and 33 studies were finally included in the review. We recorded the study, participants, intervention, disaster and other relevant data on Excel in duplicate. We conducted a meta-analysis separately for intervention-control and before-after studies using Review Manager 5.4. The Cochrane Risk of Bias tool II was used to assess risk of bias in RCTs and the risk of bias in non-randomised studies of interventions tool for quasi-experimental and before-after designs. Main outcomes were symptoms of post-traumatic stress disorder (PTSD), depression, anxiety, stress, general functioning and well-being. RESULTS: There was significant improvement in mental health symptoms following implementation of various interventions, leading to a decrease in PTSD symptoms (standardised mean difference (SMD) -2.92, 95% CI (-4.53 to -1.31), six intervention-control studies and SMD -0.71, 95% CI (-0.95 to -0.48), five before-after studies), depression symptoms (SMD -0.28, 95% CI (-0.53 to -0.03), three intervention-control studies and SMD -1.00, 95% CI (-1.41 to -0.59), 11 before-after studies), anxiety symptoms (SMD -0.38, 95% CI (-0.69 to -0.06), two studies and SMD -0.35, 95% CI (-0.47 to -0.23), eight before-after studies), stress symptoms (SMD -0.82, 95% CI (-1.10 to -0.53), two before-after studies), general functioning impairment (SMD -1.22, 95% CI (-1.73 to -0.70), three before-after studies) and an improvement in well-being (SMD 0.29, 95% CI (0.15 to 0.42), three intervention-control studies and SMD 0.67, 95% CI (0.25 to 1.09), two before-after studies). CONCLUSION: There are existing interventions to improve mental health after an EWE, and these should be integrated into all relevant disaster management plans.
30 May 2026
Read appraisal →African journal of reproductive health
Reproductive health in the digital and social age: AI, education, law, and community-based interventions.
Reproductive health has increasingly emerged as a complex, multidimensional field that extends far beyond clinical care into the domains of education, technology, law, culture, and socio-economic systems. This special issue of the African Journal of Reproductive Health brings together fifteen diverse yet interconnected papers that collectively illuminate how reproductive health outcomes are shaped by dynamic interactions across disciplines, geographies, and social structures. The contributions - spanning China, Spain, and Pakistan - underscore a unifying premise: that sustainable reproductive health improvements depend on integrative approaches that harness innovation while remaining grounded in cultural and social realities. La santé reproductive s'affirme de plus en plus comme un domaine complexe et multidimensionnel qui dépasse largement le cadre des soins cliniques pour englober l'éducation, la technologie, le droit, la culture et les systèmes socio-économiques. Ce numéro spécial de l'African Journal of Reproductive Health rassemble quinze articles divers mais interconnectés qui, ensemble, mettent en lumière la manière dont les résultats en matière de santé reproductive sont façonnés par des interactions dynamiques entre disciplines, territoires et structures sociales. Ces contributions, provenant de Chine, d'Espagne et du Pakistan, soulignent un principe unificateur : l'amélioration durable de la santé reproductive repose sur des approches intégratives qui exploitent l'innovation tout en restant ancrées dans les réalités culturelles et sociales.
30 May 2026
Read appraisal →PloS one
Risk assessment of civil aviation cabin safety incidents based on the CNN-LSTM-Attention model
Against the backdrop of the thriving global civil aviation industry, cabin safety, which is a crucial link in civil aviation safety systems, has prompted an increasingly urgent need for intelligent risk management. This study constructs an integrated framework of "deep text mining-intelligent risk assessment" and proposes a hybrid CNN-LSTM-Attention model for cabin safety incident classification. Using 8,280 global cabin abnormal event reports from 2004-2024, the model achieves 95.01% accuracy and an F1 score of 94.17% on the test set, substantially outperforming benchmark approaches. Compared with XGBoost (89.45% accuracy, 88.98% F1), the proposed model improves accuracy by 5.56% and the F1 score by 5.19%, demonstrating superior capability in extracting deep semantic features and identifying key risk patterns. The framework also establishes a "text feature-risk mechanism-hazard level" mapping system, enabling more interpretable risk quantification. The findings provide an effective technical path for intelligent early warning of cabin safety risks and offer methodological support for data-driven decision-making in civil aviation safety management.
30 May 2026
Read appraisal →JMIR formative research
Real-World Implementation of EndoConnect in Brazilian Primary Care: Formative Study of Usability, Engagement, and Equity in Digital Endometriosis Care
BACKGROUND: Endometriosis is a chronic gynecological condition affecting approximately 10% of women of reproductive age worldwide and is associated with chronic pelvic pain, infertility, and reduced quality of life. In Brazil's Unified Health System (Sistema Único de Saúde [SUS]), diagnostic delays frequently range from 7 to 10 years and disproportionately affect socially vulnerable populations, including rural, low-income, Black, and Indigenous women. Digital health interventions have been proposed as scalable solutions; however, most available applications are developed in high-income settings and do not align with the structural and operational realities of low- and middle-income countries (LMICs). OBJECTIVE: This study aimed to evaluate feasibility, usability, acceptability, and user engagement associated with the real-world implementation of EndoConnect Alpha in primary health care settings, and to explore preliminary patterns of change in symptom burden, knowledge, and care navigation. METHODS: A single-arm, prospective, formative implementation study was conducted in 10 primary health care units in Ceará, Brazil. A convenience sample of 60 participants, including women with suspected or confirmed endometriosis and primary care professionals, used the platform over an 8-week period under real-world conditions. Usability (assessed using the System Usability Scale), acceptability (assessed using the Technology Acceptance Model), engagement metrics, and exploratory outcomes were assessed. All analyses were exploratory, with no control group and no causal inference. RESULTS: High usability and acceptability were observed, with strong user engagement, including a 79% completion rate of educational modules and consistent platform use. Observed decreases in pelvic pain and anxiety were identified, alongside increases in disease-related knowledge, self-reported therapy adherence, and reported gynecological referrals. A positive association between usability and acceptability was also observed. These findings should be interpreted as exploratory signals given the study design. Descriptive subgroup analyses suggested more pronounced trends among rural participants and those with a lower education level. CONCLUSIONS: The real-world implementation of EndoConnect Alpha demonstrated high feasibility, usability, and acceptability within a public primary care setting in a middle-income country. Observed trends suggest potential benefits, particularly among underserved populations; however, causal inference cannot be established. These findings support further controlled evaluation and highlight the relevance of equity-oriented digital health strategies tailored to LMIC contexts.
30 May 2026
Read appraisal →PLoS neglected tropical diseases
Feasibility study of an AI-powered mobile app to support cutaneous leishmaniasis diagnosis in the Brazilian Amazon
BACKGROUND: Cutaneous leishmaniasis (CL) remains a major public health challenge, especially in Brazil's Amazon, where environmental and economic pressures sustain transmission. Delayed diagnosis drives morbidity, stigma, and costs. Community health workers are pivotal yet under-equipped for early triage. Artificial intelligence, effective in dermatologic imaging, is underused for CL; feasible, offline clinical tools could accelerate referral and timely care. This study aimed to evaluate the feasibility of an AI-assisted tool for early CL triage in the Brazilian Amazon by: (i) developing an AI model for CL identification from clinical skin lesion images; (ii) integrating the model into an offline-optimized mobile application for resource-limited settings; and (iii) conducting initial, real-world clinical validation. METHODS: Exploratory, IRB-approved feasibility study. Retrospective images from Brazilian Amazon sites informed a two-stage AI pipeline (lesion segmentation+classification) integrated into an offline mobile app. Multicenter validation in ideal- and real-world scenarios. Primary metric AUC-ROC; secondary sensitivity/specificity. One-sided tests: AUC-ROC [Formula: see text]0.70; ideal-world sensitivity [Formula: see text]0.75. RESULTS: For the Classification Model, 64 images were assigned to the test set while 1,160 were used for training and validation (80:20 split), with DenseNet121 yielding the highest accuracy of 0.88. The full AI pipeline (Segmentation and Classification models) achieved an accuracy of 0.81, an F1-score of 0.80, an AUC-ROC of 0.90, and a sensitivity of 0.76. In the ideal-world analysis, sensitivity reached 0.92, the F1-score was 0.84, and specificity was 0.42. CONCLUSIONS: We demonstrate the feasibility of an offline, AI-assisted mobile tool to support triage and referral for cutaneous leishmaniasis in the Brazilian Amazon. Performance reflects preliminary, descriptive point estimates from an initial diagnostic accuracy assessment and should be interpreted with caution; the tool is not intended for standalone diagnosis. Next steps include prospectively powered clinical validation, usability refinements, and regulatory evaluation, including alignment with ANVISA requirements in Brazil. Overall, this work represents an initial step toward closing the gap in clinically supported diagnostic tools for neglected tropical diseases in resource-constrained settings.
30 May 2026
Read appraisal →Journal of breath research
Investigating short-term lung inflammation using exhaled breath VOCs from exposure to candles: a randomized controlled crossover study among young mild asthmatics
Lung inflammation is associated with a response to pollution or irritants and is reported to release volatile organic compounds (VOCs) in breath, that can be monitored non-invasively. An approach to studying short-term lung inflammation is exposure to environmental emissions. This study used brief exposure to PM₂.₅ emissions from two types of burning candles to evaluate potential differences in airway inflammation among mildly asthmatic individuals. The aim was to explore VOCs linked to lung inflammation by exposure to candle emissions; emissions from candle A, a newly developed candle with a smaller emission to the surroundings and candle B, a well-characterised commercially available candle. Seventeen non-smoking asthmatics (11 female) with a mean age of 21.9 years participated in a randomised controlled double-blind crossover study including two exposure sessions: i) air with candle A emissions (mean PM2.554.1µg m-3), and ii) air with candle B emissions (mean PM2.598.4µg m-3). Participants underwent two five-hour, double-blind exposure sessions in a controlled climate chamber, each involving emissions from one of two candle types. Exhaled breath was collected at baseline (0 h), immediately post-exposure (5 h), and the following morning (24 h). VOCs were analysed using both a targeted panel of 23 predefined compounds and an untargeted workflow, which yielded 21 breath-derived VOCs after ambient-blank filtering. Statistical comparisons used Wilcoxon signed-rank tests with Benjamini-Hochberg correction. Across both exposure sessions, ten exhaled VOCs showed significant changes between baseline and immediate post-exposure (5 h), including increases in several aldehydes and decreases in selected sulfur-containing compounds. These changes were not present at 24 h, where samples resembled baseline profiles. The ten VOCs were identified from a combined dataset of 23 targeted compounds and 21 untargeted breath-derived VOCs; only the untargeted analysis yielded significant findings after correction. PCA demonstrated clear separation between baseline and 5 h samples, particularly for candle B, for which 0 h, 5 h and 24 h samples formed distinct clusters. This candle-specific response produced a multi-VOC signature capable of distinguishing individuals immediately after exposure, suggesting that exhaled VOCs can reflect short-term airway inflammatory responses. The findings suggest that an emission-specific, exhaled breath, multi-VOC profile can detect individuals exposed to inflammation triggers, such as candles. This indicates that VOCs could serve as biomarkers for detecting short-term airway inflammation, as evidenced by the systematic difference in VOCs observed 5 h after exposure to candle B. This research contributes to the advancing field of VOC-based health monitoring and might affect public health implications.
30 May 2026
Read appraisal →Journal of medical Internet research
Using the NASSS-Complexity Assessment Tool to Evaluate the Implementation of "Cadê O Kauê?": Chat-Story Intervention for Youth Participation in Mental Health Promotion in Brazil
BACKGROUND: The global public health challenge of young people's mental health is particularly evident in Brazil, which is considered the most anxious and the fifth most depressed country globally. In response to this, a digital intervention, that takes the form of a storytelling chatbot named "Cadê o Kauê?" (translation: "Where is Kauê?"), was coproduced by an interdisciplinary team of researchers, young people, and narrative designers as part of a project titled Engajadamente. The intervention was designed to strengthen Brazilian adolescents' skills in promoting their peers' mental health through direct support and collective action for mental health. The intervention was rolled out in select schools in Brazil and online via social media, but it encountered challenges during the initial implementation phase in school settings. OBJECTIVE: This project's primary objective is to evaluate the implementation of "Cadê o Kauê" in school settings in Brazil, assess current and potential complexities, and formulate recommendations to reduce or manage these complexities. The secondary objective of this project is to understand the current and potential sociotechnical change resulting from the implementation of the "Cadê o Kauê" in a real-world setting. METHODS: The Non-adoption, Abandonment, Scale-up, Spread, Sustainability (NASSS) framework was selected as the theoretical framework to identify different areas of complexity across domains and further thinking of ways to reduce or manage these complexities. Data were gathered by conducting semistructured online interviews with the Engajadamente team members based in the United Kingdom and Brazil. The NASSS-Complexity Assessment Tool was used as a sensemaking device to facilitate a collective understanding of the implementation, and narratives were mapped onto specific NASSS domains. Key themes were identified across overarching domains using thematic analysis to meet the objectives of this evaluation. RESULTS: The results mapped onto the NASSS domains generated a narrative about the initial implementation of "Cadê o Kauê?" in schools. Existing and potential complexities across technology, organization, and wider system domains were characterized by interdependencies, unintended consequences, and uncertainties. The implementation of "Cadê o Kauê?" highlighted challenges related to internet dependency, infrastructure limitations, and varying levels of organizational readiness, teacher preparedness, and school culture. Addressing these through offline solutions, additional teacher training, whole-school engagement strategies, and a value-informed complexity approach can enhance accessibility, alignment with school priorities, and adaptability within Brazil's dynamic sociopolitical context. CONCLUSIONS: Using the NASSS framework, the evaluation captured both current and emerging complexities in implementing "Cadê o Kauê?" in schools. By engaging with theory-informed approaches to technology implementation projects and deep-diving into discursive dynamic interactions between technology and its "context" of implementation, we have explored ways to manage these complexities and developed suitable recommendations to guide the Engadajamente team and support similar projects in the future.
29 May 2026
Read appraisal →Human vaccines & immunotherapeutics
Comparison of safety and immunogenicity between high-dose and low-dose quadrivalent influenza vaccines in children aged 6-35 months in China: A randomized, double-blind clinical study
Influenza vaccines for children aged 6-35 months are typically low-dose (0.25 mL, 7.5 μg hemagglutinin per strain). However, studies have shown that high-dose influenza vaccines (0.5 mL, 15 μg hemagglutinin per strain) can enhance protective efficacy without increasing the risk of adverse reactions. We conducted a randomized, double-blind clinical study in children aged 6-35 months in China. A total of 3,000 participants were randomized (1:1:1) to receive two doses of either an investigational high-dose quadrivalent influenza vaccine (H-QIV), an investigational low-dose quadrivalent influenza vaccine (LQIV-01) or a commercially available low-dose quadrivalent influenza vaccine (LQIV-02). Hemagglutination inhibition (HI) antibody titers 30 d post-vaccination were measured and vaccine safety and tolerability within 6 months post-vaccination were evaluated in these participants. The primary objectives were to demonstrate the non-inferiority of investigational vaccines to the commercially available vaccine in immunogenicity and to compare the H-QIV to L-QIVs. Both investigational vaccines demonstrated non-inferiority, with their seroprotection rates (SPRs), seroconversion rates (SCRs) and geometric mean titers (GMTs) meeting immunogenicity criteria. The H-QIV exhibited >11-fold increases in GMTs against H1N1, H3N2, B/Yamagata and B/Victoria strains compared to pre-vaccination levels, with SPRs exceeding 95% and SCRs exceeding 89%. The H-QIV was superior to both L-QIVs as it induced a stronger immune response to influenza viruses. All vaccines showed comparable safety profiles. The H-QIV can provide greater protection and benefits to this high-risk population.
29 May 2026
Read appraisal →JMIR research protocols
Evaluating the Effectiveness of an Enhanced Early Childhood Development Program Integrated Into Primary Health Care in China: Protocol for a Cluster Randomized Controlled Trial
BACKGROUND: Early childhood development (ECD) programs refer to policies and programs aimed at protecting young children's rights to achieve their full potential. Parenting interventions are effective at improving children's cognitive development and overall well-being. However, there is limited evidence on how to effectively implement and integrate such programs into routine service delivery at scale. The Government of China launched the ECD program in 2013 and the ECD scale-up program in 2023. OBJECTIVE: Our study aims to design, implement, and evaluate an enhanced ECD program embedded in the primary health care system in order to provide ECD policy recommendations for future national scale-up. METHODS: This study involves a multicenter cluster randomized controlled superiority trial in 3 counties with different levels of socioeconomic development in China. Fifty-eight clusters will be randomly assigned in a 1:1 ratio to intervention and control groups, stratified by county. In each cluster, 18 families with children aged 6-23 months will be recruited. Our intervention aims to implement an enhanced ECD program in primary care facilities. Intervention group participants will receive usual care alongside enhanced ECD services, including improved facilities, capacity building, and improved ECD services (age-adapted clinical consultations on nutrition and stimulation, age-specific parenting group sessions, home visits, and referrals for children in need). Moreover, an electronic data platform will be used. Control group participants will receive usual care. Our primary outcome is children's overall development, as measured by the Global Scale of Early Development combined form at 12 months of follow-up. Evaluation data will be collected in both arms. Additionally, a process evaluation and an incremental cost-effectiveness analysis will be conducted. Primary analysis will follow the intention-to-treat principle, and it will use generalized estimating equations to assess the population average intervention effect, with adjustment for corresponding baseline outcomes, selected individual variables, county, cluster variables, and variables differing at baseline. Qualitative data will be collected through semistructured interviews and focus groups, guided by the Capability, Opportunity, Motivation, and Behavior framework to explore implementation-related factors. Data will be transcribed for analysis using NVivo 14 (Lumivero). Ethical approval has been obtained from the Institutional Review Board of Shanghai Children's Medical Center Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS: This study was funded in 2023 and registered in April 2024. The recruitment of 1044 participants was completed on September 14, 2024. Data collection was completed on January 31, 2026. CONCLUSIONS: We aim to design an enhanced ECD service delivery model that can be embedded into the routine primary health care system. The study findings will guide government policies and reforms for strengthening the health system to scale up ECD services. Furthermore, this project may provide policy evidence to support countries in establishing or expanding their ECD services.
29 May 2026
Read appraisal →Journal of medical Internet research
Digital Literacy and Interpersonal Trust as Predictors of Willingness to Share Patient-Generated Health Data Among Korean Internet Users: Cross-Sectional Study Using Privacy Calculus and Communication Privacy Management Theories
BACKGROUND: The proliferation of wearable devices and advances in data analytics are accelerating the adoption of personalized digital health care, relying heavily on patient-generated health data (PGHD). However, the sensitive nature of this data creates significant privacy boundaries. While previous research has focused on rational cost-benefit trade-offs, there is a limited understanding of how social and cognitive factors-specifically interpersonal trust and digital literacy (DL)-shape the data-sharing decisions of the general public. OBJECTIVE: This study aims to identify the factors predicting individuals' willingness to share health data (WS) by integrating privacy calculus and communication privacy management theories. It specifically examines the comparative influence of DL, interpersonal trust, and moral motivation on data-sharing decisions. METHODS: We analyzed data from the 2023 Korea Panel Survey on the Digital Society (n=4518), a nationwide representative sample of internet users. Survey-weighted structural equation modeling with weighted least squares mean and variance adjusted estimation was used to examine the relationships among perceived risk (PR), perceived benefit (PB), DL, interpersonal trust, and WS. RESULTS: PR was the strongest negative predictor of WS (standardized coefficient [std β]=-0.189, P<.001), whereas PB was the strongest positive predictor (std β=0.076, P=.009), followed by moral motivation (std β=0.062, P=.03) and interpersonal trust. DL showed a significant negative direct association with willingness to share (std β = -0.060, P<.001). However, subdimension analysis revealed heterogeneous mechanisms: the "understanding" dimension was associated with lower PR and indirectly promoted sharing, whereas use and engagement were associated with higher PR. Age-stratified analyses suggested potential heterogeneity in these relationships, although the overall interaction was not statistically significant. CONCLUSIONS: PBs and risks were the strongest determinants of PGHD sharing, with benefits increasing and risks decreasing willingness to share. Beyond this risk-benefit balance, DL (particularly understanding) and interpersonal trust also played important roles, highlighting the need for trust-based and user-centric strategies to promote PGHD sharing and support the expansion of digital health care.
29 May 2026
Read appraisal →BMJ open
Role of community pharmacy in the prevention of cardiovascular disease in minority ethnic groups in the UK including barriers and facilitators: a mixed-methods systematic review
OBJECTIVES: To evaluate the role of community pharmacy in the prevention of cardiovascular disease (CVD) among minority ethnic groups and to identify key barriers and facilitators influencing engagement with pharmacy-based CVD prevention services. DESIGN: Systematic review using thematic synthesis to analyse both qualitative data and narratively synthesised quantitative data taking a convergent data synthesis approach. Searches were conducted from inception to 16 October 2024 across CINAHL Ultimate (EBSCOhost), EMBASE (Ovid), PubMed (NLM), Scopus (Elsevier) and Web of Science (Clarivate), supplemented by Google Scholar for grey literature and backward and forward citation tracking to identify additional studies. SETTING: Community pharmacy settings across multiple countries, including the UK and international contexts. PARTICIPANTS: Minority ethnic groups accessing community pharmacy services and community pharmacy professionals involved in delivering CVD prevention interventions. INTERVENTIONS: Community pharmacy-based CVD prevention interventions, specifically services addressing CVD risk factors. OUTCOME MEASURES: Outcomes comprised qualitative insights, including barriers and facilitators to engagement with community pharmacy-led CVD prevention services. RESULTS: Twenty-three studies met the eligibility criteria. Five overarching themes were identified: trust, systemic barriers, culturally tailored language, cultural and religious influences and family and social networks. Community pharmacies undertook varied CVD-related roles, most commonly CVD screening and diabetes management with additional contributions to smoking cessation, weight and lipid management, health promotion and medication adherence. Community pharmacies showed potential to support CVD prevention among minority ethnic groups. However, engagement was limited by language barriers, cultural beliefs, lack of trust in healthcare providers and organisational constraints such as time pressures and limited training. Facilitators included culturally tailored interventions, language concordance and strong pharmacist-patient relationships. CONCLUSIONS: Evidence from the UK remains limited, highlighting a need for further research into the role of community pharmacy in reducing CVD disparities among minority ethnic groups. International evidence suggests significant potential for pharmacy-based interventions, but improved cultural competence, targeted service design and greater awareness of determinants of equitable healthcare are essential. Future research should focus on optimising culturally responsive pharmacy-led CVD prevention strategies. PROSPERO REGISTRATION NUMBER: CRD42024579766.
29 May 2026
Read appraisal →European respiratory review : an official journal of the European Respiratory Society
Validating exacerbations of asthma in electronic health records: a systematic review
BACKGROUND: Previous studies have shown that the algorithms and code lists used to define asthma exacerbations vary across different sources of data, if reported at all. Defining and validating asthma exacerbations in electronic health records (EHR) would help to improve future research on asthma using EHR by leading to more consistent and comparable evidence. METHODS: We systematically reviewed the literature to evaluate studies that define exacerbations of asthma in EHR and report which algorithms have the highest validity. An adapted version of the QUADAS-2 designed for this review was used to assess risk of bias. RESULTS: Of the studies yielded by the search, only five met the inclusion criteria. Eligible studies used algorithms that contained codes from versions or modifications of either the 9th or 10th revisions of the International Statistical Classification of Diseases and Related Health (ICD-9 or ICD-10), and validity scores varied. Using the ICD-9 code 493 within algorithms to detect asthma exacerbations, sensitivity scores varied from 44.8% to 91.28% and specificity was >85%. Using the ICD-9 code 493.xx as the principal and secondary diagnosis in claims data, validity measures were all >85%. Using the ICD-10 code J45, scores for sensitivity, specificity and negative predictive value were also all >85%. CONCLUSIONS: Algorithms have been used to identify asthma exacerbations in EHR with varying degrees of validity. Algorithms including the ICD-9 code 493.xx or the ICD-10 code J45 to detect asthma exacerbations had high validity scores. However, there was a risk of bias in these studies and urgent work is needed using robust methods to validate definitions for future research using EHR.
29 May 2026
Read appraisal →JMIR mHealth and uHealth
Effects, Acceptability, and Use of a Dynamically Tailored Mobile What Do You Drink Intervention to Reduce Excessive Drinking Among Adolescents and Young Adults in the Netherlands: Randomized Controlled Trial
BACKGROUND: Excessive alcohol consumption among adolescents and young adults is a serious health problem. Dynamically tailored interventions could reduce their excessive drinking. We therefore developed "What Do You Drink" (WDYD), a 17-week dynamically tailored mHealth (mobile health) intervention providing personalized support on alcohol consumption. OBJECTIVE: We aim to evaluate the effectiveness, acceptability, and use of WDYD in reducing alcohol consumption of adolescents and young adults at risk. METHODS: We conducted a 2-arm, parallel-group randomized controlled trial using ecological momentary assessments. Recruitment was via an educational alcohol program, an online lifestyle monitor, social media advertisements, or news items on websites. Participants downloaded the standalone WDYD app, and when having given active informed consent, were randomized to the intervention or control group. Participants in the intervention group received dynamically tailored feedback sessions on alcohol consumption (wk 0-5, 7, 9, 13, and 17) and goal-monitoring reminders. Both groups completed an online baseline survey, 2 follow-up surveys (wk 9 and 33), and various ecological momentary assessments (7 daily assessments during wk 1, 7, 13, 19, 25, 31, and 33). Participants provided consent before randomization, in which they were informed that 2 study groups existed. After randomization, no disclosure of group assignment was provided, although participants could potentially infer it from receiving tailored sessions vs no tailored sessions. Primary outcomes were excessive drinking, binge drinking, and weekly alcohol consumption. Secondary outcomes were intrinsic motivation, self-confidence, and mood. Acceptability of WDYD was measured by survey questions; use was tracked via app data logs. RESULTS: Analyses were based on data from 1767 participants; 720 in the intervention group and 1047 participants in the control group. Almost half of them were female (2276/4795, 47.5%), and most (3471/4595, 72.4%) participants were aged 18-24 (median 19.40, IQR 2.92) years. The dropout rate was high, up to 96% (4603/4795) in the final 33rd week. No significant effect of WDYD was found on primary outcomes and mood, except for week 1 (excessive drinking: standardized β=-0.35, SE 0.15; 95% CI -0.64 to -0.05; binge drinking: standardized β=-0.36, SE 0.16; 95% CI -0.68 to -0.04; mood: standardized β=0.20, SE 0.06, 95% CI 0.08 to 0.32). Both groups reduced their alcohol consumption. Significant positive effects were found for intrinsic motivation and self-confidence up to 25 weeks (wk 25: standardized β=0.54, SE 0.24; 95% CI 0.06 to 1.02 for motivation; standardized β=0.72, SE 0.26; 95% CI 0.22 to 1.23 for self-confidence). Participants evaluated WDYD as acceptable and usable. CONCLUSIONS: WDYD did not significantly reduce excessive drinking compared to control, but improved motivation and self-confidence. High dropout rates highlight challenges in sustaining engagement in long-term mHealth interventions. Future research should explore strategies to enhance retention and optimize dynamic tailoring.
28 May 2026
Read appraisal →JMIR formative research
Differences in Safety Risks Across Languages in Health-Relevant Queries: Vulnerability Analysis of Large Language Model Responses
BACKGROUND: Large language models (LLMs) such as ChatGPT are increasingly used to support health-related queries and decision-making. However, these models can be "jailbroken" through adversarial prompts that bypass safety filters and elicit harmful or medically inappropriate responses. In health care contexts, such vulnerabilities pose serious risks. Understanding how jailbreak susceptibility varies across languages is essential for developing robust safeguards and promoting equitable access to safe health information. This paper may contain examples that may be deemed harmful in terms of violence, self-harm, and drug abuse. OBJECTIVE: This study aims to systematically compare and contrast the vulnerability of a health LLM for jailbreaking across 3 languages: English, Spanish, and Hindi (transliterated using the Latin alphabet), based on emoji and permutation cipher attacks. METHODS: We analyzed 1000 input prompts per language, drawn from the BeaverTails dataset, across 3 harm categories: self-harm, violence, and drug abuse. Each prompt was modified using emoji and permutation cipher techniques, resulting in 6000 input-output pairs. Model responses were evaluated by human coders to determine the success rate of jailbreak attempts across languages and cipher types. RESULTS: Hindi prompts showed the highest vulnerability, with 787 successful jailbreaks using emoji ciphers and 873 using permutation ciphers. Spanish and English followed, with lower success rates across both cipher types. Differences in jailbreak success across languages and cipher strategies were statistically significant. Additionally, attacks targeting violence-related prompts were more successful overall than those targeting drug-related or self-harm content, indicating variation in vulnerability by harm type. CONCLUSIONS: The findings of this formative study reveal that LLM safety performance varies substantially across languages and harm categories, raising concerns about equitable protection in multilingual health communication. Disparities in access to harmful content may contribute to downstream health risks. Strengthening multilingual content moderation and developing language-aware safety mechanisms are critical steps toward creating safer and more inclusive health AI systems.
28 May 2026
Read appraisal →PloS one
Determinants of maternal postnatal care utilization in Bangladesh: A machine learning and SHAP-based analysis of BDHS 2022 data
Postnatal care (PNC) plays a crucial role in minimizing maternal and neonatal morbidity and mortality, but the uptake of services in Bangladesh remains below the recommended level. Although logistic regression has been widely used, it may miss complex nonlinear interactions among social, economic, and healthcare factors. This study contributes to the body of knowledge by using machine learning (ML) to identify the most significant determinants of PNC and to enhance prediction accuracy. We compared logistic regression to several ML models, including Random Forest, XGBoost, CatBoost, Support Vector Machine, AdaBoost, and Gradient Boosting, using nationally representative data from the 2022 Bangladesh Demographic and Health Survey (BDHS) with ADASYN oversampling to correct class imbalance. Among all models, Random Forest achieved the highest AUC (0.9050), closely followed by XGBoost (0.9036) and CatBoost (0.9028), all of which substantially outperformed logistic regression (AUC = 0.8470). SHAP analysis of the Random Forest model indicated that delivery place, husband's occupation, rural residence, wealth index, and media exposure were the most influential predictors of PNC utilization, alongside maternal education, women's occupation, and age-related factors. The results indicate that ML is more effective than classical procedures for revealing latent patterns and making accurate predictions. Policy implications include encouraging facility-based deliveries, improving maternal education, reducing wealth disparities, and enhancing media coverage of health, particularly among rural and low-income groups. This paper not only identifies key drivers of PNC in Bangladesh but also demonstrates how ML can supplement traditional methods to reinforce maternal health policy and interventions.
28 May 2026
Read appraisal →Journal of the American College of Cardiology
Combining Genomics With Lipid and Inflammatory Biomarkers to Predict Coronary Artery Disease Risk: UK Biobank Study
BACKGROUND: Coronary artery disease (CAD) polygenic risk score (PRS), low-density-lipoprotein cholesterol (LDL-C), lipoprotein(a) (Lp(a)), and high-sensitivity C-reactive protein (hsCRP) are biomarkers that predict CAD. It is unclear whether integrating genomics with lipid and inflammatory biomarkers could complement traditional risk scores in identifying people at risk of CAD. OBJECTIVES: This study assesses the predictive value of CAD PRS, LDL-C, Lp(a), and hsCRP for incident CAD across different age and sex groups. METHODS: Participants (n = 215,695) from the UK Biobank aged 40 to 69 years with baseline CAD PRS, LDL-C, Lp(a), and hsCRP values were followed for 12 years to assess the incidence of CAD. We evaluated a multivariable-adjusted Cox model that included all 4 biomarkers, net reclassification index, C-statistics, and population attributable risk across different age and sex groups. RESULTS: Over a 12-year follow-up, 4,721 men and 2,425 women developed CAD. The HRs for incident CAD associated with each biomarker elevation were 1.79 (95% CI: 1.70-1.89) for CAD PRS, 1.60 (95% CI: 1.48-1.66) for LDL-C, 1.20 (95% CI: 1.12-1.29) for Lp(a), and 1.64 (95% CI: 1.57-1.72) for hsCRP. CAD PRS demonstrated a stronger association in men (HR per SD: 1.49; 95% CI: 1.45-1.54) than women (HR per SD: 1.37; 95% CI: 1.31-1.44; P-interaction ≤ 0.001). All biomarkers conferred greater HRs at younger ages (P < 0.0001). Individuals with all biomarkers elevated had a 4.65-fold increased risk of CAD compared with those with no elevated biomarkers. A combined 4-biomarker model had a higher C-statistic of 0.753 compared with the pooled cohort equations (C-statistic of 0.740). The C-statistic of the combined 4-biomarker model was also higher in younger individuals in both sexes and yielded a 32.0% continuous net reclassification index when compared with the pooled cohort equations. CONCLUSIONS: CAD PRS, LDL-C, hsCRP, and Lp(a) show independent age- and sex-specific associations with CAD. Measuring all 4 biomarkers may improve midlife CAD risk prediction for both male and female patients.
28 May 2026
Read appraisal →Cancer causes & control : CCC
Built environment (BE) and cancer: a systematic review of the BE's impact during the treatment journey and patient outcomes
The role of the built environment (BE) in cancer research has been extensively explored in prevention, focusing on its influence as a determinant of exposure to carcinogens and a lifestyle shaper, particularly through geographic accessibility to resources like transportation, healthy food, and diagnostic centers. However, the BE's role and influence during the treatment period and its connection with patient outcomes remain comparatively understudied. This systematic review employed the CDC definition of BE, following PRISMA guidelines and AI-driven software (ASReview) for a thorough and efficient literature review. A total of 31 articles were identified (27 database, 4 snowballing) that examined the BE's role during the treatment phase. These studies investigated diverse BE characteristics including urban features (e.g., transportation, green environment, food environment) and architectural features (e.g., design, aesthetics) during the cancer patient treatment journey. Among the included studies, the most analyzed outcomes were Physical Activity (PA) (11 articles), followed by survival and mortality (9 articles). Findings revealed positive associations between specific BE characteristics-such as green spaces, accessibility, transportation options, and aesthetics-and cancer patients' physical activity levels, quality of life, and mental health status; however, findings are inconsistent. These results underscore the potential of integrating urban and architectural BE analysis to enhance the psychosocial dimensions of cancer treatment, improve healthcare delivery, and open new pathways for research strategies.
28 May 2026
Read appraisal →BMJ open
Prevalence of teenage pregnancy and associated factors in Uganda: a meta-analysis and systematic review
OBJECTIVE: Teenage pregnancy is a major public health problem with huge consequences for maternal health and pregnancy outcomes. This calls for a concerted effort from different stakeholders involved in issues of teenagers' sexual reproductive health to achieve the SDG target of 2030 on the reduction of maternal mortality. The objective of this systematic review was to estimate the prevalence of teenage pregnancy and its associated factors in Uganda. DESIGNS: We conducted a systematic review and random-effects meta-analysis according to Preferred Reporting Items for Systematic Review and Meta-analysis standards. DATA SOURCES: After prospective registration (PROSPERO CRD42023486460), a literature search was conducted in PubMed, African Journals Online and Google Scholar in December 2023. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Observational studies that reported the prevalence of teenage pregnancy among teenagers were included. DATA EXTRACTION AND SYNTHESIS: Articles were screened for relevance at the title, abstract and full-text levels by multiple reviewers. The quality of studies was independently appraised using the Joanna Briggs Institute Critical Appraisal Checklist and Newcastle-Ottawa Scale. Any discrepancies were resolved by reaching a consensus. The process of extracting data included study information, geographical categorisation, type of studies, population, sample size, results/outcomes and prevalence of teenage pregnancy. The risk of bias was determined by Egger's test. The results were pooled using random-effects models to calculate the prevalence of teenage pregnancy with a CI of 95% and I² statistic. RESULTS: Of 918 records screened, 10 studies (4143 participants) were included. The pooled prevalence of teenage pregnancy was 25.5% (95% CI 13.7% to 39.5%; I²=98.9%), with individual study estimates ranging widely from 3.0% to 56.4%, reflecting substantial heterogeneity across study settings, populations and periods of data collection. Higher estimates were observed in the Central-Eastern region (31.7%, 95% CI 19.5% to 45.1%). The overall certainty of evidence was rated as very low using the Grading of Recommendations, Assessment, Development and Evaluation framework, primarily due to very serious inconsistency across included studies (I²=98.9%). CONCLUSIONS: Pooling studies of mixed quality revealed a slightly higher prevalence of teenage pregnancy in Uganda. This review provides valuable insight for policymakers and healthcare providers in developing interventions and policies to reduce the burden of teenage pregnancy from disadvantaged backgrounds. PROSPERO REGISTRATION NUMBER: CRD42023486460.
28 May 2026
Read appraisal →Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Psychological distress in cancer survivors: a population-based analysis and machine learning-based risk stratification
PURPOSE: As the number of cancer survivors increases, psychological distress has become an important issue. Using nationally representative data, we evaluated mental health outcomes among Korean cancer survivors compared with cancer-free controls and developed models to identify individuals at risk of psychological distress. METHODS: We analyzed data from the Korea National Health and Nutrition Examination Survey (KNHANES) from 2007 to 2021. Psychological outcomes were assessed using standardized questionnaires, and a composite distress outcome was constructed. Risk stratification models were developed among cancer survivors using logistic regression and machine learning algorithms, including random forest, XGBoost, LightGBM, support vector machines, k-nearest neighbors, and naïve Bayes. RESULTS: A total of 88,061 participants were included, comprising 3733 cancer survivors and 84,328 cancer-free controls. Compared with cancer-free controls, cancer survivors had higher odds of depressed mood (OR 1.33; 95% CI 1.18-1.51), suicidal ideation (OR 1.14; 95% CI 1.00-1.31), suicide planning (OR 1.91; 95% CI 1.37-2.65), and mental health counseling (OR 1.36; 95% CI 1.08-1.71). Among cancer survivors, multiple models were evaluated, with logistic regression showing the highest performance (AUROC 0.689), followed by XGBoost (0.686). In logistic regression, longer working hours, depression history, activity limitation, female sex, smoking, employment, low income, and distorted body image were independently associated with distress. SHAP analysis identified activity limitation, sex, and depression history as key factors. CONCLUSIONS: Cancer survivors experience increased psychological distress across multiple outcomes. Machine learning-based models may help identify individuals at higher risk of psychological distress, supporting risk-based assessment in survivorship care.
28 May 2026
Read appraisal →Journal of chemical information and modeling
Machine Learning-Driven Simulations of the SARS-CoV-2 Fitness Landscape from Deep Mutational Scanning Experiments
Predicting protein variant effects is a key challenge in preparing for pathogenic viral strains, understanding mutation-linked diseases, and designing new proteins. Protein sequence-structure-function relationships are difficult to model due to complex allosteric and epistatic effects. To investigate efficient modeling strategies, we trained supervised machine learning (ML) models with deep mutational scanning (DMS) libraries of SARS-CoV-2 receptor binding domain (RBD) sequences labeled with angiotensin converting enzyme 2 (ACE2) binding affinity. These models demonstrate superior performance predicting combinatorial mutation effects compared to adding or averaging the effects of point mutations and exhibit strong extrapolative performance ranking omicron variants when training only near wild type (WT) variants. We characterize the RBD fitness landscape by combining ML with Markov Chain Monte Carlo simulations to predict evolutionary patterns from the WT sequence. These generate comparable sequence profiles to high-fitness sequences in DMS data and predict mutations in unseen omicron variants. These models provide insight into the relationship between RBD sequence elements and offer a new perspective on the use of DMS to predict emerging viral strains, which we anticipate will be applicable to other evolutionary prediction tasks. To facilitate application and future development of this strategy, we introduce Mavenets: https://github.com/SztainLab/mavenets.
27 May 2026
Read appraisal →Global health action
Integrating GIS and local knowledge for optimised medical supply prepositioning in flood-prone Nigeria: a strategic framework
BACKGROUND: Nigeria faces recurring flood disasters that severely disrupt its healthcare systems and delays medical relief efforts. Current medical supply prepositioning by the National Emergency Management Agency (NEMA) remains inadequate due to infrastructure limitations, funding constraints, and poor coordination. OBJECTIVE: To develop and validate a Strategic Medical Hub Locator Framework that integrates Geographic Information Systems (GIS) analysis with qualitative local knowledge to optimise medical supply prepositioning for flood emergencies in Nigeria. METHODS: We employed a mixed-methods approach, combining qualitative analysis of 22 GIS-based flood risk studies in Nigeria and structured expert survey responses from 34 professionals with flood response experience, including five with direct NEMA warehouse experience. The framework was grounded in Disaster Risk Reduction theory and supported by Protection Motivation Theory and Theory of Planned Behaviour. RESULTS: The framework identified eight strategic medical hub locations: six existing NEMA warehouses (Abuja, Lagos, Kano, Gombe, Maiduguri, Kaduna) with the strongest performance, and two new strategic sites (Akure and Uyo) to address service gaps in South-South and South-East regions. Abuja emerged as the highest-performing hub with a composite score reflecting good centrality, governance capacity, and operational readiness. The framework successfully bridged data silos between spatial flood risk patterns and operational constraints. CONCLUSIONS: Integration of GIS thematic analysis with qualitative local data provides a viable, replicable method for enhancing humanitarian medical logistics in flood-prone regions. The Strategic Medical Hub Locator Framework offers a structured decision-support tool that can inform evidence-based investment in Nigeria's disaster health infrastructure, while being adaptable to other Global South contexts. Key findings: Where primary geospatial data silos are present, GIS analysis can be enhanced by combining it with local qualitative insights, thereby bridging the gap between technical modelling and practitioner realities.Added knowledge: The paper offers a methodological contribution through the design of a Strategic Medical Hub Locator Framework that is replicable in contexts where primary data and complex modelling are not feasible.Global health impact for policy and action: This study provides policymakers and humanitarian actors with a proof-of-concept decision-support tool. The exploratory framework offers a scalable model that can be adapted to other flood-prone settings where primary data and practical knowledge are scattered, thereby strengthening disaster preparedness and health system resilience strategies.
27 May 2026
Read appraisal →Proceedings of the National Academy of Sciences of the United States of America
Systemic electioneering from the evangelical pulpit: Evidence from a computational analysis
Religious institutions' engagement in prohibited electoral advocacy is a growing concern for democratic governance. In the United States, such mobilization has been especially visible within the evangelical movement. We examine this phenomenon using a corpus of 88,546 sermons from predominantly evangelical churches, transcribed from 63,683 h of Sunday services spanning the 2020, 2022, and 2024 election cycles and a nonelection control period. Analysis of this corpus reveals that direct political advocacy and endorsements are widespread: 14.7% of churches engaged in this speech during the three months surrounding the 2024 election. This behavior follows a clear electoral rhythm, peaking on the Sunday before Election Day, when 3.5% of churches mobilized. Geographic analysis indicates that advocacy correlates with county partisan composition but lacks strategic targeting; rates in swing states are indistinguishable from those in safe states. Our results provide large-scale quantification of political speech from American pulpits that constitutes prohibited electioneering under current Internal Revenue Service (IRS) guidelines, revealing a pattern of base mobilization driven by local partisan context rather than national electoral strategy.
27 May 2026
Read appraisal →Journal of perinatal medicine
Effect of preterm birth on neonatal, infant, child, young adult and adult mortality: a systematic review and meta-analysis
OBJECTIVES: Preterm birth is associated with a higher risk of mortality. In 2020, the global incidence of preterm births was reported at 9.9 per 100 live births. This meta-analysis was undertaken to evaluate the effect of preterm birth on mortality among various age groups. METHODS: A thorough search was done on four electronic databases: "PubMed, Scopus, Web of Science, and Embase". Adhering to PRISMA 2020 guidelines, observational analytical studies published till 4th December 2024 were included. Screening of the studies was done by two independent reviewers in two stages: title/abstract, followed by full text review of the advanced articles. It was followed by data extraction. Study quality was assessed with the Newcastle Ottawa Scale. Meta-analysis using a random-effects model was done in R Studio. PROSPERO ID: CRD42024622282. RESULTS: Database search yielded 1775 unique studies. 23 studies met the final predefined eligibility criteria. Preterm babies showed an increased risk of mortality compared to term babies with a pooled relative risk of 6.12 (95 % CI: 3.16-11.84) for neonatal mortality, 11.84 (95 % CI: 6.88-20.37) for infant mortality and 1.88 (95 % CI: 1.24-2.83) for 1-5 year. However, it was similar in adult mortality with a pooled relative risk of 1.21 (95 % CI: 0.07-20.12). CONCLUSIONS: Preterm birth is strongly associated with increased risks of childhood mortality, especially in extreme and very preterm infants, but the risk persists even for late preterms.
27 May 2026
Read appraisal →Scientific reports
Depressive symptoms are a key determinant of health-related quality of life in ICU survivors with psychological distress
Survivors of critical illness frequently experience persistent impairments in health-related quality of life (HRQoL), with psychological symptoms contributing substantially to this burden. The relative contribution of co-occurring depression, anxiety, and post traumatic stress symptoms remains insufficiently understood. To address this gap, we conducted a cross-sectional analysis of pre-randomization data from the PICTURE randomized controlled trial, a multicenter study of a brief primary care-based psychological intervention for post-traumatic stress disorder symptoms following critical illness, including 319 intensive care unit survivors. Clinical, demographic, and mental health assessments were obtained after ICU discharge. Latent profile analysis, random forest modeling, and quantile regression were applied to identify determinants of HRQoL measured by the EuroQol Five-Dimension Five-Level (EQ-5D-5L) index and visual analog scale (VAS). The mean EQ-5D-5L index was 0.71 (SD 0.27; median 0.81) and the mean EQ VAS score was 60.7 (SD 19.4; median 60.0), indicating considerable overall impairment. Depression, anxiety, and post-traumatic stress symptoms showed substantial overlap and formed four distinct symptom profiles associated with specific functional impairments. Screening positive for depression on the 2-item Patient Health Questionnaire (PHQ-2) with ≥ 3 points was associated with a median reduction of -0.13 (95% CI -0.19 to -0.07) on the EQ-5D-5L index and -12.45 points (95% CI -17.93 to -6.96) on the EQ VAS, exceeding clinical and demographic predictors. These findings indicate that depressive symptoms are a major determinant of impaired health related quality of life among intensive care survivors with psychological distress and support routine brief depression screening in post-intensive care follow up.Trial registration: ClinTrials.gov: NCT03315390 (Registration date: 2017-10-20); German Clinical Trials Register: DRKS-ID: DRKS00012589 (Registration date: 2017-10-17).
26 May 2026
Read appraisal →Journal of perinatal medicine
Early kangaroo care in preterm ≤32 weeks and very low birth weight infants: a systematic review and meta-analysis
OBJECTIVES: Kangaroo care (KC), involving skin-to-skin contact, early breastfeeding and early discharge, demonstrated benefits in improving outcomes for preterm and low birth weight infants. This systematic review and meta-analysis aimed to evaluate the effectiveness of early KC (initiated within the first 24 h) vs. conventional neonatal care in very preterm infants (≤32 weeks) and/or very low birth weight (VLBW) infants (<1,500 g). METHODS: A comprehensive search of MEDLINE, SCOPUS, Web of Science, and CENTRAL databases was conducted. Randomized controlled trials (RCTs) comparing early KC to conventional care in very preterm and/or VLBW infants were included. Risk of bias was assessed using the Cochrane Risk of Bias tool. Meta-analysis was conducted using R, with relative risks (RR) and 95 % confidence intervals (CI) calculated. RESULTS: Four RCTs, encompassing 1,679 newborns, were included. Meta-analysis revealed a significant reduction in mortality risk (RR=0.81, 95 % CI: 0.67-0.98) with early KC. The pooled RR for infection risk was 0.89 (95 % CI: 0.77-1.02). The impact on hypothermia was mixed, with moderate heterogeneity observed. CONCLUSIONS: Early KC may reduce mortality and morbidity in very preterm and VLBW infants although its effects on hypothermia vary by severity. Further studies are required to assess its effects on infants weighing <1,000 g or born before 28 weeks of gestation.
26 May 2026
Read appraisal →Journal of medical Internet research
Association Between Wearable Device Adoption and Health-Related Lifestyle Behaviors: Retrospective Cohort Study
BACKGROUND: Wearable devices are increasingly adopted for personal health monitoring, but evidence on their long-term associations with health-related lifestyle behaviors in real-world population settings remains limited. OBJECTIVE: This study examined the longitudinal association between wearable device adoption and engagement in health-related lifestyle behaviors using a nationally representative panel dataset from South Korea. METHODS: We analyzed data from the 2016 and 2022 waves of the Korea Media Panel survey. Health-related lifestyle behaviors in the physical, social, and cultural domains were operationalized as estimated annual activity counts based on self-reported frequency measures. We used a difference-in-differences framework with generalized estimating equations to compare changes in these behaviors between new wearable adopters and nonadopters adjusting for demographic and socioeconomic characteristics. Relative changes were estimated using Poisson models with a log link, and subgroup analyses were conducted to explore variation across sociodemographic groups. As a sensitivity analysis, inverse probability of treatment weighting was additionally applied to assess the robustness of the findings to observed baseline imbalance. RESULTS: Wearable device adoption was associated with greater increases in total, physical, and cultural health-related lifestyle activities over time. In the difference-in-differences model, adopters showed greater relative increases in total activity (rate ratio [RR] 1.24, 95% CI 1.08-1.35), physical activity (RR 1.36, 95% CI 1.12-1.64), and cultural activity (RR 1.78, 95% CI 1.31-2.42) than nonadopters. Subgroup analyses showed limited evidence of consistent heterogeneity and should be interpreted cautiously. Sensitivity analyses using inverse probability of treatment weighting showed overall patterns broadly similar to those of the primary analyses. CONCLUSIONS: In this nationally representative panel study, wearable device adoption was associated with greater increases in total, physical, and cultural health-related lifestyle activities over time, whereas no clear association was observed for social activity. These findings should be interpreted as associative rather than causal given the observational design and the inability to directly assess parallel trends.
26 May 2026
Read appraisal →Current obesity reports
How Have Researchers Estimated the Impact of Excess Weight on Mortality? A Systematic Review.
OBJECTIVE: The aim of this review is to describe and reflect on the methodology of the studies that estimate the attributable mortality (AM) to excess weight. The purpose was to provide a methodological framework and serve as a starting point to improve the estimation of AM to excess weight. This will lead to more comparable estimates over time and across countries. METHODS: A systematic review was conducted considering MEDLINE (Ovid), Embase and Web of Science databases. Studies that had estimated AM to excess weight published until December 2024 were included. Data extraction was performed in an ad-hoc table based on the STREAMS-P tool, and a descriptive analysis of the methodology employed was performed. RESULTS: The search strategy yielded 2,163 results. Twenty-three studies estimating AM in four continents were included. The majority estimated AM to all-cause mortality (n = 9) and for cardiovascular diseases (n = 9), followed by cancer without specifying which type of cancer (n = 7). Variation was observed in the body mass index (BMI) cut-off points used to define overweight, obesity and excess weight. Thirteen studies applied the population attributable fraction (PAF) formula denoted by PAF = [P (RR-1)] / [1 + P (RR-1)]. Most of the relative risks (RR) derived from meta-analysis (n = 14), and only a minority studies (n = 6) used RR from national studies based on the population for which AM was estimated. CONCLUSION: This review emphasizes methodological constraints on AM estimation to excess weight. Causes of death causally associated with excess weight should be prioritized rather than relying solely on all-cause mortality. The ideal scenario would be to consider lag times; RR derived from the population under study and to use WHO BMI cut-offs and measured data rather than self-reported weight and height. The absence of this data should not prevent AM estimation if limitations are acknowledged. Expanding available estimates worldwide is essential to improve understanding of the mortality burden associated with excess weight.
26 May 2026
Read appraisal →Renal failure
Unveiling the role of air pollution in diabetic kidney disease: an integrated study combining network toxicology, machine learning, and Mendelian randomization
Diabetic kidney disease (DKD) is a major and severe complication associated with diabetes. Air pollution is not only an independent risk factor for metabolic disorders but also an "accelerator" of DKD progression. This study seeks to investigate the molecular pathways connecting air pollution to DKD. Multiple databases were integrated to obtain potential target genes of 10 common air pollutants. The gene expression omnibus (GEO) database was employed to acquire DKD datasets. Differential expression analysis and weighted correlation network analysis (WGCNA) were performed to identify DKD-related genes. 12 machine learning algorithms were utilized to generate 113 unique predictive models, which were employed to select hub genes. Subsequently, MR, single-cell, gene set enrichment analysis (GSEA), and immune infiltration analyses were performed, followed by molecular docking of hub genes with air pollutants. A total of 714 targets were identified from 10 air pollutants, and 80 potential targets were identified from DKD transcriptomic data. Machine learning methods identified 5 hub genes that are closely associated with DKD. Mendelian randomization (MR) analysis indicated that, among the five hub genes, only NOS3 demonstrated a statistically significant causal association with DKD. Immune infiltration analysis found that hub genes were closely related to immune cells. Molecular docking validation indicated that certain air pollutants can stably bind with hub genes such as NOS3 and PTGS2. Air pollutants may be linked to alterations in various biological processes, potentially involving key genes such as ADH5, CASP3, NOS3, PTGS2, and SDHB, including potential metabolic reprogramming, inflammatory processes, and immune microenvironment changes.
26 May 2026
Read appraisal →European journal of pediatrics
Safety and efficacy of liposomal iron for iron deficiency anemia in pediatric population: A systematic review and meta-analysis of randomized controlled trials
Iron deficiency anemia (IDA) remains a public health problem in children. Conventional iron therapy is effective but often causes gastrointestinal adverse effects that reduce adherence. Liposomal iron has been developed to enhance absorption and improve tolerability. This systematic review and meta-analysis evaluated the efficacy and safety of liposomal iron compared with conventional iron formulations in pediatric patients with IDA. We searched PubMed, Scopus, Web of Science, and the Cochrane Library up to February 21, 2026 for randomized controlled trials (RCTs) comparing liposomal iron with conventional oral iron in children with IDA. Analyses were performed using R software with the meta package. Continuous outcomes were pooled as mean differences (MDs) and dichotomous outcomes as risk ratios (RRs) with 95% confidence intervals (CIs) using a random-effects model. Subgroup analyses according to follow-up duration. Four RCTs involving 454 children were included. At 6 months, liposomal iron produced a significantly greater increase in hemoglobin compared with conventional iron (MD 0.96 g/dL, 95% CI 0.09-1.82; P = 0.03), although heterogeneity was substantial (I2 = 92.9%). No significant differences were observed at earlier time points. Liposomal iron significantly reduced total iron-binding capacity (MD - 35.52 μg/dL; P < 0.0001) and increased mean corpuscular hemoglobin (MD 1.83 pg; P < 0.0001). Liposomal iron was associated with fewer adverse events (RR 0.29; P = 0.02) and lower risk of constipation (RR 0.56; P = 0.02).Conclusion: Liposomal iron offered better tolerability and was non-inferior to conventional iron for most hematologic outcomes. Evidence remains preliminary and larger RCTs are needed to confirm its efficacy in pediatric IDA.
26 May 2026
Read appraisal →Circulation journal : official journal of the Japanese Circulation Society
Regional Disparities in Access to Specialized Facilities and Prescription Preference for Initial Pulmonary Arterial Hypertension Treatment - A Nationwide Study Using the National Database of Health Insurance Claims
BACKGROUND: Improved prognosis of pulmonary arterial hypertension (PAH) has been reported from specialized facilities, though nationwide patient access to both specialized centers and initial treatment regimen in Japan remains unclear. METHODS AND RESULTS: The study group comprised patients with PAH defined as having disease-specific ICD-10 code, administration of medications and diagnostic testing between 2012 and 2023 in the National Database of Health Insurance Claims. Among 13,228 patients across the country, 30.7% accessed Japan Pulmonary Hypertension Registry facilities and 23.7% were initiated with disease-specific combination therapy, though numbers varied across regions. CONCLUSIONS: Regional disparities in access to disease-specific specialized treatment for PAH need to be addressed.
25 May 2026
Read appraisal →Lancet (London, England)
Updated trends in the global prevalence and burden of mental disorders, 1990-2023: a systematic analysis for the Global Burden of Disease Study 2023
BACKGROUND: The 2023 iteration of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) estimated prevalence, incidence, and health burden for 375 diseases and injuries, including 12 mental disorders. We assess past, current, and emerging trends in the prevalence and burden of mental disorders across sexes and age groups, for 21 regions, 204 countries and territories, and by Socio-demographic Index (SDI) quintile, from 1990 to 2023. METHODS: Mental disorders included in GBD 2023 were anxiety disorders, major depressive disorder, dysthymia, bipolar disorder, schizophrenia, autism spectrum disorders, conduct disorder, attention-deficit hyperactivity disorder, anorexia nervosa, bulimia nervosa, idiopathic developmental intellectual disability, and a residual category of other mental disorders. A literature review identified epidemiological data for each disorder. These were analysed via a Bayesian meta-regression to estimate prevalence by disorder, sex, age, location, and year. Disorder-specific prevalence was multiplied by disability weights representing the severity of health loss associated with each disorder to estimate years lived with disability (YLDs). Deaths due to anorexia nervosa were assessed with a Cause of Death Ensemble modelling strategy to estimate deaths by sex, age, location, and year, and then multiplied by the standard life expectancy at age of death to estimate years of life lost (YLLs). YLDs equalled disability-adjusted life-years (DALYs) for all mental disorders except anorexia nervosa (the only mental disorder considered as an underlying cause of death in GBD), for which DALYs represented the sum of YLDs and YLLs. We presented prevalence, deaths, YLDs, YLLs, and DALYs as counts, age-specific rates per 100 000 population, and age-standardised rates per 100 000 population. FINDINGS: We estimated 1·17 billion (95% uncertainty interval 1·06-1·31) prevalent cases of mental disorders globally in 2023, equivalent to an age-standardised prevalence rate of 14 210·7 cases (12 849·5-15 940·1) per 100 000 population. These estimates represented a 95·5% (75·0-121·2) increase in prevalent cases and 24·2% (11·4-41·4) increase in age-standardised prevalence rate between 1990 and 2023. All mental disorders showed increases in prevalent cases between 1990 and 2023, while notable increases were seen in age-standardised prevalence rates for anxiety disorders, major depressive disorder, dysthymia, anorexia nervosa, bulimia nervosa, schizophrenia, and conduct disorder. There were an estimated 171 million (127-228) DALYs due to mental disorders globally across sex and age in 2023, equivalent to an age-standardised DALY rate of 2070·5 DALYs (1519·1-2750·5) per 100 000 population. Mental disorders contributed to 6·1% (4·8-7·6) of all-cause DALYs in 2023, making them the fifth leading cause of global DALYs (up from 12th in 1990). DALYs were almost entirely composed of YLDs. Mental disorders were the leading cause of YLDs in 2023 (up from second in 1990), explaining 17·3% (14·8-20·6) of all-cause global YLDs. Leading causes of mental disorder DALYs were anxiety disorders (ranked 11th among the 304 diseases and injuries at Level 4 of the GBD cause hierarchy), major depressive disorder (15th), and schizophrenia (41st). Globally in 2023, mental disorder age-standardised DALY rates were higher among females (2239·6 [1643·7-3014·1] per 100 000) than among males (1900·2 [1399·8-2510·8] per 100 000), and peaked in the 15-19 years age group (2617·3 [1850·6-3696·8] per 100 000). All locations showed increased mental disorder DALY rates in 2023 compared with 1990, ranging across countries and territories from 1302·4 (952·7-1683·7) per 100 000 in Viet Nam to 3555·8 (2661·9-4715·0) per 100 000 in the Netherlands. Across SDI quintiles, DALY rates ranged from 1853·0 (1352·1-2469·3) per 100 000 for middle SDI to 2184·1 (1606·1-2890·3) per 100 000 for high SDI. INTERPRETATION: A significant health burden was imposed by mental disorders in all countries and territories in 2023, irrespective of the health resources available. In some instances, this burden has increased over time and is unevenly distributed across populations. Stronger surveillance systems, particularly in low-income and middle-income countries, are required. Additionally, we need more coordinated and inclusive policies to reduce the burden through early treatment and prevention, tailored to sex and age differences across locations. Responding to the mental health needs of our global population, especially those most vulnerable, is an obligation, not a choice. FUNDING: Gates Foundation, Queensland Health, and University of Queensland.
25 May 2026
Read appraisal →Environmental monitoring and assessment
XGBoost-based analysis of short- and long-term COVID-19 air quality impacts in Tehran, Iran.
This study examines the air quality trends associated with COVID-19 lockdowns and the subsequent recovery on air quality in Tehran, employing an established XGBoost framework for de-weathering with daily data from 22 monitoring stations from 2019 to 2025. A comprehensive analysis was conducted on six principal pollutants (PM₂.₅, PM₁₀, NO₂, O₃, SO₂, and CO) across four distinct temporal phases: Pre-pandemic, Pandemic, Post-COVID, and After Termination. While the model effectively reduced meteorological bias, exhibiting strong efficacy for particulate matter (R = 0.78-0.88; IOA = 0.68-0.88; FAC2 > 0.95), we explicitly acknowledge less consistent outcomes for reactive gases such as O₃ (R < 0.75; NMGE > 0.30). The imposition of lockdown measures coincided with significant reductions in pollutants associated with vehicular traffic: NO₂ exhibited a decline of - 30 to - 36%, PM₂.₅ decreased by - 18 to - 22%, and CO diminished by - 20%. In contrast, O₃ experienced an increase of + 20-30%, indicative of diminished NO titration. Principal Component Analysis (PCA) corroborated these trends, with PC1 (NO₂, PM₂.₅, CO) accounting for approximately 60% of the variance throughout the pandemic. In subsequent phases, partial recoveries were noted: PM₂.₅ escalated by + 15-20%, NO₂ stabilized at around -10%, SO₂ consistently decreased (-30% by 2025), whereas O₃ surged by + 20% by 2025, clustering with PM₁₀ in PC2, thereby highlighting the impacts of dust and secondary formation processes. Lockdowns yielded transient enhancements in air quality, with restricted long-term advantages. Sustainable progress necessitates the adoption of comprehensive policies targeting traffic, industrial emissions, VOCs, and dust management.
25 May 2026
Read appraisal →European journal of pediatrics
Associations of socioeconomic status and nurturing environment with developmental outcomes in very preterm children without sensorimotor impairment: a secondary analysis of the INTACT study
UNLABELLED: The objective of this study is to retrospectively evaluate the associations between socioeconomic status (SES), including nurturing environment, and developmental quotients (DQ) at age 3 in children born very preterm with birth weight ≤ 1500 g. This secondary analysis used follow-up data from the Improvement of NICU Practices and Team Approach Cluster Randomized Controlled Trial. Participants born < 32 weeks' gestation without major sensorimotor impairments were stratified into three groups: 22-24, 25-27, and 28-31 weeks. Multiple linear regression evaluated the associations between prenatal SES and DQ scores of the Kyoto Scale of Psychological Development (KSPD), adjusted for sex, parity, gestational age, small for gestational age, multiple births, and facilities. Post-discharge SES variables were subsequently added to assess associations with nurturing environment. Of 2148 eligible survivors, 1978 underwent KSPD testing and 1846 caregivers completed SES questionnaires. Higher parental education was positively associated with total DQ across all groups: 22-24 weeks (β = 2.246, 95% CI 0.015-4.477), 25-27 weeks (β = 1.589, 95% CI 0.408-2.770), and 28-31 weeks (β = 1.299, 95% CI 0.315-2.282). Group childcare utilization was associated with higher total DQ: 22-24 weeks (β = 3.397, 95% CI 0.893-5.901), 25-27 weeks (β = 1.851, 95% CI 0.591-3.111), and 28-31 weeks (β = 2.617, 95% CI 1.613-3.620). These associations remained after adjustments for postnatal morbidities. CONCLUSION: Among children born very preterm without major sensorimotor impairments, parental education and group childcare utilization were independently associated with more favorable cognitive outcomes at age 3. These results suggest the importance of socioeconomic and environmental support in optimizing developmental outcomes for this vulnerable population. WHAT IS KNOWN: • Prenatal and postnatal SES are associated with developmental outcomes in both preterm and term children. In addition, daily group childcare environments influence child development in the general population. WHAT IS NEW: • Among very preterm children without major sensorimotor impairments, including those born at 22-24 weeks' gestation, parental education and group childcare utilization are independently associated with more favorable cognitive and language outcomes at age 3.
25 May 2026
Read appraisal →Chemico-biological interactions
Carbon quantum dots exacerbate Parkinson's disease-like pathology through microglia-mediated neuroinflammatory responses with toxicological implications
The global burden of Parkinson's disease (PD) is projected to double by 2050, with early-onset cases demonstrating accelerated progression and limited therapeutic options. Recently, carbon quantum dots (CQDs) emerge as promising nanoplatforms for PD theragnostic, but their paradoxical role in exacerbating neuroinflammation and neurodegeneration shows the urgent need for mechanistic safety evaluations to bridge their therapeutic potential and neurotoxic risks. This study conducted a neuro-safety assessment of CQDs based on MPP+-induced mice and cell PD models to stimulate the theragnostic scenarios of CQDs in PD patients in the real-world. The results showed that CQDs not only promoted the onset and progression of PD-like damages in mice and cells but also exacerbated PD-related neurological dysfunction and structural damages in PD models. The microglia-mediated neuroinflammatory reactions were identified to be pivotal mediators of CQDs exacerbating PD-like damages based on machine learning (ML) approaches. According to these key toxic targets, we established molecular docking technology and network pharmacology to propose interventional strategies, including functional modification of CQDs and anti-neuroinflammatory drugs to alleviate the exacerbation of PD-like damages induced by CQDs, thereby ensuring the safe application of CQDs in the diagnosis and treatment of PD.
25 May 2026
Read appraisal →Medicine
Effect of a sports-medicine-guided football program on physical fitness in adolescents: A controlled school-based trial
Integrating artificial intelligence (AI) with sports medicine principles into school-based physical education may enhance physical fitness and reduce injury risk among adolescents. This study aimed to evaluate whether a 10-week sports-medicine-guided football curriculum augmented with explainable machine-learning feedback produces greater improvements in physical fitness and injury-prevention outcomes than a standard physical-education curriculum. A total of 195 healthy junior high school students (mean age 14.1 ± 0.7 years) participated in a controlled school-based intervention and were allocated to either an AI-supported sports-medicine curriculum (intervention) or a standard curriculum (control). Physical fitness outcomes, including lung capacity, estimated maximal oxygen uptake (VO2max), sprint performance, standing long jump, and middle-distance running performance (800 m girls/1000 m boys), were assessed before and after the 10-week program. Outcomes were analyzed using 2-way mixed analysis of variance to test Group × Time interactions. Injury risk prediction was supported by an explainable machine-learning ensemble model (CatBoost + Gradient Boosting) interpreted using SHAPley Additive explanations. Significant Group × Time interactions were observed for lung capacity (P < .01) and VO2max (P < .01), indicating greater improvements in the intervention group compared with controls. The intervention group also demonstrated superior improvements in sprint performance, middle-distance running, and lower-limb power (P < .05), while no significant between-group differences were observed for upper-body strength (P > .05). A school-based football curriculum integrating sports-medicine principles with explainable AI-driven feedback leads to significantly greater improvements in key physical-fitness outcomes than a standard physical-education curriculum. This approach directly supports individualized training adaptation and injury-risk awareness, offering a scalable model for enhancing adolescent health and safety in school physical education.
25 May 2026
Read appraisal →BMC psychology
Single-exposure messages for child sexual abuse prevention: a randomized controlled online trial testing educational and humanizing approaches
BACKGROUND: Child sexual abuse and exploitation, including online material depicting such acts, constitute a major public health concern. Prevention efforts likely benefit from public understanding and destigmatization, yet communication strategies on this topic face persistent misconceptions and strong emotional reactions. This randomized controlled online study examined whether brief educational and humanizing communication interventions influenced knowledge, attitudes, and behavioral intentions related to prevention, while avoiding adverse emotional or ethical effects. METHODS: A total of 2,019 adults from Spain and Portugal were recruited via an online panel and randomly assigned to one of four conditions: an educational message, a humanizing message with empathy focus, a humanizing message with prevention focus, or a neutral control message. Each intervention consisted of a short video and accompanying text presented as part of a health information campaign. Measures included affective state, stigma-related attitudes, literacy about therapeutic options, openness toward the topic, and behavioral intention to seek information. RESULTS: Exposure to any intervention message led to short-term changes in affective responses, with lower positive valence and slightly higher arousal compared to the control group (medium effect for valence, small for arousal). No significant differences emerged for stigma dimensions, knowledge, openness, or behavioral intentions. All three intervention formats performed similarly. The study did not identify measurable short-term adverse or rebound effects on stigma. Dropout rates did not differ across conditions, but languages. CONCLUSIONS: Brief communication interventions elicited short-term affective responses without evidence of increased stigma or avoidance on the measured outcomes. While the present single exposures appear insufficient to change attitudes or behavior, such formats may serve as a foundation for repeated, multi-channel prevention messaging integrated into broader educational efforts. TRIAL REGISTRATION: German Clinical Trials Register (DRKS), DRKS00038927, retrospectively registered on 09/01/2026.
25 May 2026
Read appraisal →Current urology reports
Association Between Ambient Temperature and Urolithiasis: A Systematic Review and Meta-analysis
PURPOSE OF REVIEW: The global incidence of urolithiasis has risen in recent decades. Emerging evidence suggests that higher ambient temperatures are linked to an increased risk of kidney-stone-related events, including acute renal colic, likely through physiological mechanisms such as increased urinary calcium excretion and greater supersaturation of calcium oxalate and calcium phosphate. This study aims to systematically review existing evidence on the relationship between ambient temperature and urolithiasis risk. RECENT FINDINGS: Of 892 records identified, 46 studies met the inclusion criteria for the systematic review, and 16 were included in the meta-analysis. Most studies reported a positive association between higher ambient temperatures and increased kidney stone-related events, with seasonal peaks occurring during summer months in the Northern Hemisphere and from December to March in Australia. Considerable heterogeneity was observed in exposure definitions, meteorological data sources, outcome ascertainment, and lag structures. Reported effect estimates ranged from RR 1.10 to 2.54. Meta-analysis showed that higher ambient temperature was associated with an increased risk of urolithiasis presentation (pooled RR 1.31, 95% CI 1.21-1.43; I²=86.7%). Subgroup analyses showed pooled RRs of 1.27 (95% CI 1.18-1.37) for stone colic, 1.33 (95% CI 1.06-1.67) for emergency visits, and 1.36 (95% CI 0.98-1.90) for hospitalizations. Associations were stronger at medium and long lag periods than at short lags. Most studies were rated as high risk of bias, primarily because of confounding and outcome measurement concerns. Sensitivity analyses supported the robustness of the findings. This systematic review highlights an association between higher ambient temperatures and increased presentations for kidney stone disease. Addressing environmental factors may be a valuable strategy for reducing nephrolithiasis incidence.
25 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Training a Smoking Status Probabilistic Model Using Cotinine Levels in a Large Claims Database
INTRODUCTION: Smoking status is an important confounder for many epidemiologic studies, yet it is not well documented in common sources of real-world data, including administrative claims. Probabilistic models can be used to create a proxy for smoking status, yet most published models have been trained using self-reported data. The objective of this study was to train a smoking status probabilistic model using cotinine values available in a large claims database. METHODS: Beneficiaries were included if they had at least one cotinine measurement and were categorized as a "current smoker" if their serum or plasma cotinine value was ≥5 ng/mL or urine cotinine value was ≥30 ng/mL. Predictors were collected across one year prior to the cotinine assessment date. The model was fit using logistic regression with stepwise forward selection. Model performance was assessed using discrimination and calibration. RESULTS: The final model yielded an area under the receiver operating characteristic curve of 0.77 (95%CI:0.75-0.78) and was well calibrated across most prediction deciles. The strongest predictors included diagnosis codes for smoking and drug abuse, and number of medications. The model was found to be highly specific, yet not sensitive at probability cutoffs ≥0.2. CONCLUSIONS: A smoking status model was developed and internally validated for application in claims data, using available cotinine values to define smoking status and found to have acceptable discrimination and calibration. The model is based on 26 predictors, fewer than other similar published smoking status models. External validation of the model should be a next step toward utilizing the model for epidemiological research. IMPLICATIONS: This study tests the utility of cotinine values to validate a smoking status probabilistic model, which has not been done in the literature to date. The results were robust to various cotinine levels used to define smoking status, per current guidance. The final model uses only 26 factors to predict smoking status, simplifying the application of the model in other claims databases.
25 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Patterns of e-Cigarette Use and Smoking Cessation Outcomes: Secondary Analysis of a Large Randomised Controlled Trial to Inform Clinical Advice
INTRODUCTION: Limited data exist on how to use e-cigarettes (EC) to optimize smoking cessation. METHODS: We examined associations between patterns of EC use and outcomes at 1 year in a large trial (N = 886) comparing nicotine replacement therapy (NRT) and EC. RESULTS: Use of tobacco flavor was limited and associated with a lower smoking cessation rate compared to other flavors (relative risk; RR = 0.56, 95% CI = 0.35 to 0.89). EC users reduced nicotine strength over time. Abstainers using EC reported lower urges to smoke than abstainers using NRT at both weeks 1 (b = -0.25, 95% CI = -0.45 to -0.04) and 4 (b = -0.37, 95% CI = -0.58 to -0.16). Participants using both cigarettes and EC (dual users) at week 1 were more likely to stop smoking at week 4 than exclusive smokers (RR = 4.45, 95% CI = 1.96 to 10.10). Dual users at 4 weeks and 6 months were also more likely to achieve validated 50% reduction in smoke intake at 1 year (RR = 2.37, 95% CI = 1.36 to 4.11 and RR = 4.56, 95% CI = 2.71 to 7.66, respectively). CONCLUSIONS: Non-tobacco flavors were preferred and may be also more effective. Urges to smoke were lower in EC users than in users of NRT. Dual use was associated with a reduction in smoking and quitting smoking later on. IMPLICATIONS: Clinicians advising smokers wanting to use EC as a quitting aid can consider recommending non-tobacco flavors; explaining that EC reduce urges to smoke more than combination NRT; and reassuring those worried about dual use that such use is associated with reduced smoking and a higher chance of stopping smoking altogether later on.
25 May 2026
Read appraisal →Science advances
Generalizability of an AI-based mammogram risk score (MRS) for breast cancer among diverse populations of women
Conventional prediction models incorporating genetic and clinical factors including breast density underperform in non-European populations. We investigated an artificial intelligence-derived mammogram risk score (MRS), a summary of texture features that captures intrinsic breast-tissue characteristics-the substrate for cancer development. This study leveraged data from two North American screening cohorts totaling >226,000 women, including non-Hispanic white, non-Hispanic Black, East Asian, South Asian, and Indigenous women. MRS distributions showed nonsignificant shifts (and similar SDs) between cohorts and across race and ethnic subgroups. MRS increased with age and was significantly associated with breast cancer risk, with hazard ratios per SD ranging from 2.24 [95% confidence interval (CI), 2.03 to 2.46] to 2.32 (95% CI, 2.25 to 2.39) after age adjustment. Associations remained significant within all subgroups. Calibration was excellent across the racial and ethnic groups and across full-field digital mammograms and tomosynthesis. These findings establish MRS as a strong predictor that is independent of race or ethnicity, demonstrating its potential for broader clinical utility.
24 May 2026
Read appraisal →PloS one
Views, barriers, and facilitators of people living with human immunodeficiency virus and healthcare professionals regarding the use of a mobile health application to improve HIV self-care in Malaysia
AIM: The views, barriers, and facilitators of people living with HIV (PLWH) and healthcare professionals (HCPs), regarding the use of a mobile health application (m-HA) to improve HIV self-care were explored. SUBJECT AND METHODS: Seventeen PLWH, nine doctors and two nurses who owned a smartphone and understood English or Malay were recruited from the infectious disease clinic of a tertiary hospital in Malaysia. Semi-structured in-depth interviews were conducted face-to-face using a topic guide, audio-recorded and transcribed verbatim. Data was analysed using reflexive thematic analysis. Two researchers independently coded transcripts and met to resolve discrepancies and develop themes. Data collection continued until thematic saturation was achieved. RESULTS: Three themes emerged: (1) Perceived benefits and concerns regarding m-HA usage: participants perceived m-HA could improve knowledge, but expressed concerns regarding information overload. Participants viewed m-HA as a means to enhance access to hospital services like clinic visits, medication refills, communication with HCPs, and medical records documentation. However, concerns regarding misuse, data confidentiality and security remained. (2) Perceived motivators of m-HA: participants perceived that high utilitarian and hedonic motivators increase m-HA usage. (3) Perceived influences to use m-HA: participants believed PLWH would use m-HA if introduced by their peers or HCPs. CONCLUSION: These findings provided information for developing a patient-centred m-HA to improve HIV self-care in Malaysia.
24 May 2026
Read appraisal →BMJ paediatrics open
Enhancing parental health knowledge through digital knowledge mobilisation tools: a randomised controlled trial and qualitative study
OBJECTIVE: To assess the effectiveness of blogshots (ie, image-based digital knowledge mobilisation tools) to increase knowledge and manage expectations with respect to six Choosing Wisely Canada (CWC) recommendations about common childhood conditions. DESIGN: Multimethod study including a non-pharmacological randomised controlled trial and qualitative interviews. SETTING: Online questionnaires and semistructured interviews across Canada. PARTICIPANTS: Parents or legal guardians of children under 5 years. INTERVENTION: Participants were randomly allocated to receive one of two sets of blogshots whereby a blogshot on a new CWC topic was delivered weekly over 3 weeks (Group A: pharyngitis (diagnosis), common cold, asthma; Group B: pharyngitis (treatment), bronchiolitis, otitis media). Study investigators were blinded to participant allocation. Baseline and follow-up (week 5, month 3, month 6) questionnaires were administered. Qualitative interviews contextualised intervention data. MAIN OUTCOME MEASURES: The primary outcome was change in knowledge. Secondary outcomes were change in expectations, intentions, actions over time and usability of the blogshots. RESULTS: 167 participants (n=133 (80%) mothers) were included in the final analysis (group A, n=85; group B, n=82). Baseline knowledge scores did not differ between groups. At follow-up 1, those who received the blogshot for a given topic scored significantly higher (p<0.001, d=0.30) on knowledge questionnaires, compared with those that did not. No differences were observed in knowledge scores between groups at follow-up 2 and 3. Participants expressed intentions to use the blogshots (eg, share with friends, physicians), as well as actions (eg, wait/watch approach vs seek healthcare) to manage their child's condition. Qualitative data (n=13 interviews) showed that blogshots are aesthetically pleasing and contain easy to read and understandable information. CONCLUSIONS: Blogshots can be an effective tool to disseminate child health information to parents. Due to the online dissemination, this approach could be scaled to a broader international level and applied to different health topics that are relevant across the world. TRIAL REGISTRATION NUMBER: NCT06005337.
24 May 2026
Read appraisal →Medicine
Tech-based evaluation of healthcare quality during the COVID-19 pandemic
The coronavirus disease 2019 pandemic profoundly disrupted global health systems, exacerbating preexisting inequalities in access to and quality of care. Disparities in service accessibility, continuity, coordination, and comprehensiveness highlight the need for a multidimensional, data-driven approach to healthcare evaluation. We conducted a retrospective analysis using 52,490 responses from the 2021 Global Burden of Disease COVID-19 Health Service Disruption Survey. We developed a 4-dimensional evaluation framework aligned with World Health Organization principles for people-centered care. Following variable selection, standardized preprocessing, and manual labeling, we trained and assessed 6 machine learning (ML) algorithms. We further optimized the 2 best-performing models - support vector machine (SVM) and random forest (RF) - using interpolation-based data augmentation, cross-validated hyperparameter tuning, and particle swarm optimization. SVM showed the highest baseline performance (accuracy 0.93), whereas RF achieved competitive macro-F1 scores. Interpolation-based data augmentation improved the generalizability of the SVM model, increasing its accuracy to 0.96. The RF model benefited most from particle swarm optimization-based hyperparameter optimization. Model predictions revealed persistent inequalities in healthcare service quality: respondents with lower income, lower educational attainment, and rural residence were disproportionately classified as receiving lower-quality services, whereas urban residence and higher income were associated with higher-quality care. Our scalable ML framework successfully assessed healthcare service quality during the pandemic, with optimized SVM and RF models demonstrating robust performance on high-dimensional, imbalanced survey data. Post-pandemic recovery strategies must prioritize socioeconomically disadvantaged populations. Furthermore, integrating ML tools can enhance real-time quality monitoring within health systems.
24 May 2026
Read appraisal →Medicine
Global, regional, and national burden of clavicle, scapula, or humerus fracture in 204 countries and territories, 1990 to 2021: A systematic analysis from the Global Burden of Disease Study 2021
Clavicle, scapula, or humerus fracture represent a major public health challenge, yet their epidemiology and health burden remain poorly characterized. Using the Global Burden of Disease 2021 framework, we quantified incidence, prevalence, and years lived with disability (YLDs) of clavicle, scapula, or humerus fractures across 204 countries from 1990 to 2021. Estimates were stratified by age, sex, region, and socio-demographic index (SDI), and reported with 95% uncertainty intervals (UIs) from Bayesian models. Globally, the age-standardized incidence rate (ASIR) declined from 276.68 (95% UI: 219.06-346.71) per 100,000 person-years in 1990 to 220.94 (95% UI: 172.60-280.99) per 100,000 person-years in 2021, with an estimated annual percentage change of -0.78% (95% UI: -0.82% to -0.73%). High SDI regions showed the greatest ASIR (300.30 per 100,000 person-years), age-standardized prevalence rate (112.03 per 100,000 person-years), and age-standardized YLDs rate (3.72 per 100,000 person-years). In 2021, Eastern Europe had the highest ASIR (465.06 per 100,000 person-years), while Australasia led in age-standardized prevalence rate (151.42 per 100,000 person-years) and age-standardized YLDs rate (5.04 per 100,000 person-years). China ranked first in absolute prevalence (1.21 million, 95% UI: 1.04-1.39 million) and YLDs (40,235, 95% UI: 24,471-61,196). Despite declines in age-standardized rates, absolute cases increased substantially, highlighting demographic and regional disparities. Priority populations for targeted prevention include women aged ≥60 years and residents of high-SDI regions, as these strata accounted for the highest burden across incidence/prevalence/YLD rates.
24 May 2026
Read appraisal →Studies in health technology and informatics
Accessibility of Digital Health and Welfare Services Among Immigrants in Finland
Digital health and welfare services support the delivery of the services. However, the health benefits are mixed at the population level, and further research is needed to better understand the driving factors of healthcare inequalities, particularly among vulnerable subgroups, e.g., immigrants. This qualitative study aimed to understand equality in service accessibility among immigrants, especially from the informational, experiential, and institutional perspectives. Five focus group interviews were conducted for immigrants. Data was analysed with deductive content analysis. Barriers for informational accessibility included linguistic challenges and inadequate digital literacy (DL); for experiential accessibility, usability challenges and disrespectful phone services; for institutional accessibility, challenges with electronic authentication identification for personalized digital services. Facilitators for the use of digital health and welfare services included linguistic improvements of services and support for DL. Further research, including interventions with participatory design and linguistic and digital support, is needed to improve accessibility of digital services for immigrants.
24 May 2026
Read appraisal →Studies in health technology and informatics
Frameworks for Digital Health Engagement: A Scoping Review Protocol
Digital health technologies (DHTs) are increasingly integral to healthcare delivery, yet sustained engagement remains inconsistent across users and settings. This scoping review aims to map frameworks and instruments that conceptualise digital health engagement across adoption and sustained use. Searches were conducted in Scopus, Web of Science, ACM Digital Library, and PsycINFO. The review will clarify conceptual coverage and identify gaps in digital engagement.
24 May 2026
Read appraisal →Studies in health technology and informatics
Can NLP Detect Loneliness in Electronic Health Records? A Proof-of-Concept Study
Loneliness is clinically important but under-documented in electronic health records (EHRs), posing challenges for secondary use and computational phenotyping. This study evaluated whether natural language processing (NLP) methods can detect and classify loneliness severity from clinical notes. Patients with a loneliness survey (mild, moderate, severe) were identified, and notes within six months prior to the survey were retrieved. An expert-expanded lexicon was applied, and transformer models (RoBERTa, ClinicalBERT, Longformer) were fine-tuned for loneliness severity classification. Large language model-based summarization of social and psychiatric history was also tested as an alternative input representation. Performance was evaluated using accuracy, weighted-F1, and per-class F1. All models achieved modest accuracy (0.3 to 0.7), and struggled to identify severe loneliness, reflecting sparse and inconsistent documentation even among surveyed patients. While summarization marginally improved accuracy, gains primarily reflected mild predictions. Manual review of 100 social worker notes from severely lonely patients found explicit mentions of loneliness in only two cases, confirming that relevant documentation is exceedingly rare. These findings demonstrate that model performance is constrained by the sparse and inconsistent documentation of loneliness in EHRs, rather than by deficiencies in the modeling approach itself.
24 May 2026
Read appraisal →Studies in health technology and informatics
Long Covid and Digital Health in Switzerland: Potentials and Limitations
Post-COVID-19 (or Long Covid) presents a complex and persistent health challenge affecting a growing number of individuals worldwide. Digital health interventions (DHIs) offer potential support for symptom monitoring, self-management, and information access. However, their availability, quality, and sustainability remain uncertain, particularly in smaller healthcare markets such as Switzerland. This study provides a descriptive assessment of ten representative DHIs for Long Covid available from Switzerland. Each tool was evaluated using a 19-item framework derived from validated instruments. Three independent reviewers tested all interventions on iOS and Android devices, with consensus ratings across five quality categories. Results showed strong usability (average 6.3/8) and practical usefulness (5/8), but consistent weaknesses in accessibility (3.7/8) and data protection (4.6/8). Total scores ranged from 14.7 to 26.3 out of 38. Several Swiss-based apps were discontinued during the study period, highlighting market fragility. Findings underscore the need for inclusive design, transparent data practices, and institutional support if DHIs are to complement Long Covid care sustainably.
24 May 2026
Read appraisal →Studies in health technology and informatics
Digital Health Tool Usability and Redesign: Preliminary Scoping Review Findings
Few usability or user experience studies report how insights resulted in improved digital health tool (DHT) design. Therefore, this paper reports on preliminary findings of a scoping review that examines this topic. A systematic search in five databases led to the inclusion of 102 studies that met the inclusion criteria, namely those reporting both usability evaluation and redesign outcomes. Categorisation of these studies identified four user groups: patients, healthcare professionals, public health users, and mixed groups. Many DTHs were web- (36%) or mobile-based (32%) applications, and most often newly developed (68%).
24 May 2026
Read appraisal →Studies in health technology and informatics
Machine Learning Applications Within the Earlier Medicine Framework for Stroke: A Scoping Review
This scoping review explores how machine learning (ML) has been applied to stroke research within the Earlier Medicine framework, which promotes proactive and personalized care through primary (preventive care), secondary (acute care), and tertiary (chronic care) prevention levels. Following PRISMA-ScR guidelines, studies were identified from PubMed and Scopus, yielding 105 eligible studies. Most studies focused on tertiary prevention, such as predicting in-hospital mortality, complications, and functional outcomes, while fewer addressed early risk prediction or acute-phase detection. Common predictors included age, NIHSS score, glucose, stroke volume, BMI, hypertension, and diabetes, reflecting reliance on routine clinical data. Traditional ML models (e.g., logistic regression, random forest, SVM) remain dominant, although Ensemble/Hybrid and Deep Learning models have increased steadily since 2021. ML demonstrated promising predictive accuracy and clinical potential, though challenges remain in data heterogeneity, model transparency, and external validation.
24 May 2026
Read appraisal →JMIR research protocols
Protocol for Monitoring Postpartum Hypertension Outcomes via a Smartphone App (MOMitor): Ecological Momentary Assessment
BACKGROUND: Postpartum hypertension defined as elevated blood pressure after childbirth, affects approximately 20% of women after delivery. Digital health interventions that include remote monitoring therefore, present an important opportunity to facilitate regular blood pressure assessment in this high-risk population. OBJECTIVE: The primary objective is to assess within- and between-person changes in hypertension status over the first 6 weeks postpartum using a smartphone-based ecological momentary assessment protocol. The secondary objective is to characterize the trajectory of hypertension indicators across the 6-week period and to compare hypertension screening results from week one and week six within participants. METHODS: This study uses a time-series design using data from prospectively enrolled patients within a large health system. Patients eligible for recruitment were women aged 18 years or older who spoke English, owned a smartphone, had a liveborn neonate, and were willing to download an app and respond to survey questions within the app. Throughout the study period, all participants received hypertension screening items that asked whether their blood pressure was greater than 140/90 mm Hg and whether they felt dizzy or lightheaded, short of breath, or had a severe headache. A subset of participants were additionally asked to report their blood pressure readings. We estimate within- and between-participant effects using a generalized linear mixed model for a positive hypertension screen during weeks one through six. The model includes both fixed and random effects, controlling for age, race, marital status, education, insurance status, mode of delivery, total number of pregnancies, and history of diabetes mellitus. RESULTS: The study was funded July 2021 and data collection was initiated in November 2021. Data collection for this study, per protocol, was completed in June 2025, though other participants continue to be enrolled in the ongoing parent study. Data analysis is expected to be completed by Spring 2026 with publication planned for Summer 2026. CONCLUSIONS: The study findings will provide insight into trajectories of hypertension outcomes in postpartum women and the utility for smartphone app-based remote blood pressure monitoring among postpartum women whose blood pressure was regularly tracked. Findings will provide evidence to support whether widespread implementation of this digital health surveillance approach to improve outcomes in maternal health, especially in the postpartum period, is clinically warranted.
23 May 2026
Read appraisal →Journal of medical Internet research
Effectiveness of a Blended Intervention to Promote Physical Activity Among Office Employees: Randomized Controlled Trial
BACKGROUND: Regular moderate-to-vigorous physical activity (MVPA) reduces the risk of noncommunicable diseases, yet one-third of adults globally fail to meet MVPA recommendations. Office employees, among the least active groups, face heightened risks due to prolonged sedentary behavior and barriers like lack of time, fatigue, and low motivation. Although scalable, web-based interventions frequently face challenges, such as low engagement, high attrition, and limited personalization. Blended interventions, combining digital tools with interactive components, show promise but lack robust evidence among office employees. OBJECTIVE: This study aimed to evaluate the effectiveness of a theory- and evidence-based blended intervention in increasing MVPA among office employees. METHODS: This 24-week, 3-arm randomized controlled trial included 141 office employees, randomized equally into blended (web-based+electronic workshops [e-workshops]), web-based only, and control groups. The intervention was developed using the intervention mapping framework, ensuring a systematic, evidence- and theory-based design tailored to the needs of the target population. All participants accessed a study website; the control group used the "Library" module with general MVPA information, while intervention groups also accessed a tailored, theory-driven "Intervention" module. The blended group additionally attended 3 live e-workshops (weeks 2, 4, and 8). MVPA was objectively measured using hip-worn accelerometers at baseline (T1), postintervention (12 wk, T2), and follow-up (24 wk, T3). Retention, engagement, and acceptability were assessed. Analyses followed the intention-to-treat principle, and generalized linear mixed models were used to evaluate between-group differences at T2 and T3, adjusted for baseline MVPA, sex, and ActiGraph LEAP (Ametris) wear time. RESULTS: A total of 141 participants (mean age 32.1, SD 9.2 y; 75/141, 53.2% female) were randomized evenly across groups with comparable baseline characteristics, except for sex (P=.002). The blended group showed significantly greater MVPA increases than the control at T2 (β coefficient=0.247, 95% CI 0.013-0.480; P=.04) and T3 (β coefficient=0.373, 95% CI 0.139-0.607; P=.002), and greater increases than the web-based at T2 (β coefficient=0.287, 95% CI 0.062-0.512; P=.01) and T3 (β coefficient=0.368, 95% CI 0.138-0.597; P=.002). Sensitivity analyses confirmed the robustness of these findings. Retention and engagement rates were 83% and 56%, respectively. Participants reported high acceptability across all domains. CONCLUSIONS: A blended intervention integrating tailored web content with interactive e-workshops significantly increased MVPA at T2 and T3 compared with both web-based and control groups. This success stems from the rigorous intervention mapping framework, which systematically identified effective behavior change and habit formation theories, while the blended approach addressed key limitations of traditional and web-based methods. These findings underscore the potential of evidence- and theory-based blended approaches to address common barriers to MVPA and promote sustainable MVPA in workplace settings, offering promising opportunities for broader scalability and personalization.
23 May 2026
Read appraisal →Journal of medical Internet research
Measuring eHealth Literacy in the European Economic Area, Switzerland, and the United Kingdom: Scoping Review
BACKGROUND: Digital tools continue to evolve and have the potential to improve health care delivery. However, they are associated with challenges, including accessibility issues and health misinformation. Individuals need eHealth literacy (eHL) to reliably use these tools, and providers require appropriate eHL measurement approaches to offer targeted solutions. For around 2 decades, researchers have been operationalizing and measuring eHL. OBJECTIVE: This paper aims to provide an up-to-date overview of how eHL has been assessed in recent years in the European Economic Area, Switzerland, and the United Kingdom and which methodological limitations need to be considered. METHODS: A scoping review was conducted. Records were searched via CINAHL, PubMed, and Google Scholar on January 31, 2025, and January 28, 2026. Peer-reviewed empirical papers published in German or English since 2020 that measured eHL in the European Economic Area, Switzerland, or the United Kingdom were included. The synthesis covered the publication trend, eHL measurement approaches and associated limitations reported in the included papers, eHL measurement frequency, countries and languages, and samples. RESULTS: In the final analysis, 132 papers published between 2020 and 2025 were included. The number of publications per year showed an overall upward trend (2020: 11/132, 8.33%; 2025: 35/132, 26.52%). Nine self-report eHL measurement instruments were used, the eHealth Literacy Scale being the most frequent (94/132, 71.21%). All included papers (132/132, 100%) reported data collection via surveys, and digital surveys were common (71/132, 53.79%). Reported limitations included potential self-report biases (37/132, 28.03%), selection biases due to the data collection modes (26/132, 19.70%), and limitations specific to 5 eHL measurement instruments (18/132, 13.64%). Most included papers (121/132, 91.67%) reported eHL results from a single measurement per participant. Data were collected in 22 countries within the target regions. The distribution of eHL measurement instruments varied considerably between countries. Data were collected in 22 languages within the target regions. Patients or individuals with health problems were a frequent target group (64/132, 48.48%). Most papers (104/132, 78.79%) described studies covering broad adult age ranges. Sample sizes ranged from ≤50 (7/132, 5.30%) to >2000 participants (8/132, 6.06%). CONCLUSIONS: To our knowledge, this is the first scoping review synthesizing eHL measurement limitations reported in empirical papers from the European Economic Area, Switzerland, and the United Kingdom. The identified limitations reported in the included papers potentially lead to biased results. Therefore, health care providers and researchers should take various factors into account when selecting eHL measurement approaches, such as eHL measurement purpose, target population, and data collection setting. Future research should address these constraints by adapting and developing new or revised eHL measurement instruments, including translated and culturally adapted versions. Policymakers should encourage health care providers to conduct methodologically well-founded eHL measurements as a basis for targeted solutions.
23 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Mediators of the Effect of Opt-In Versus Opt-Out Treatment on Smoking Cessation in a Randomized Clinical Trial
INTRODUCTION: Smoking cessation interventions are effective. Most smokers do not receive them, in part because smokers are required to "opt-in". Changing the default (CTD) randomized clinical trial, conducted at a large academic medical center, demonstrated that CTD to providing treatment unless refused (opt-out) improved quit rates. The objective of this study was to evaluate if treatment participation and default-theory based variables explained the effect of opt-out on cessation. METHODS: We conducted a secondary analysis of CTD data (N = 739). Descriptive statistics and correlations of the baseline variables were provided. Structural equation models were employed to investigate whether the treatment assignment was causally mediated by a priori proposed mediators including perceived endorsement, counseling participation, and medication utilization. RESULTS: The mean age of the participants was 51.39 (SD = 14.71) years, among whom 349 (47.23%) were females, and the majority was White (428, 57.92%). The indirect effects from the opt-out treatment arm to counseling participation to smoking cessation (b = 0.201, 95% CI = 0.105 to 0.303), and from opt-out to perceived endorsement to counseling participation to smoking cessation (b = 0.010, 95% CI = 0.002 to 0.022) were significant. The indirect effect from opt-out to perceived endorsement to counseling participation to medication utilization to smoking cessation was marginally significant (b = .001, 95% CI = 0.000 to 0.003). CONCLUSIONS: The opt-out approach enhanced patients' sense that their counselor endorsed and/or recommended treatment, as well as counseling participation. The results partially support our hypothesis that the advantage of Opt-out care would increase treatment participation and would do so by psychological variables thought to underpin the efficacy of defaults. IMPLICATIONS: Our results strengthen evidence for the value of delivering smoking cessation as a default (opt-out rather than opt-in) by illuminating likely mechanisms of action. These include increasing participation in counseling and two default-based theoretical mechanisms, perceived endorsement and implied endorsement.
23 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Acceptability of Using Large Language Models to Support Smoking Cessation Attempts: a Qualitative Study Among African Americans Who Smoke
INTRODUCTION: African Americans face significant disparities in tobacco-related diseases and access to smoking cessation resources. Digital health interventions using large language models (LLMs) show promise in increasing engagement and successful quit attempts. However, impressions regarding acceptability of LLM-based interventions among African Americans are unknown and evidence suggests such interventions require tailoring for underserved communities. Our goal was to evaluate perceptions of LLM-based interventions among African Americans to inform development of an LLM-based chatbot to support quit attempts. METHODS: We conducted remote focus groups with adult African Americans residing in Minnesota who smoke cigarettes to determine acceptability of LLM-based health interventions and inform the functionality of an LLM-based chatbot supporting quit attempts. Discussions followed a structured guide and were recorded to facilitate analysis. Transcripts were coded independently by two analysts with a shared codebook. RESULTS: 21 adults participated in focus group discussions. 57.1% of participants were female and the mean age was 45.6 (SD, 10.5). Three themes united participants' feedback: (1) participants limited familiarity with LLM and related AI technology, (2) willingness to use an LLM-based app to support quit attempts, and (3) perceptions of features that impact the acceptability of an LLM-based chatbot to support quit attempts. CONCLUSION: African Americans have complex perceptions and expectations regarding the use of LLMs to deliver health interventions. While many recognize the potential benefits, significant concerns and knowledge gaps remain. To build trust and acceptability, intervention developers should prioritize community engagement and ethical guidelines to ensure that LLM-driven solutions are inclusive and effective for multiple communities. IMPLICATIONS: Large language models and related AI technologies have shown promise for improving access and engagement when deployed through digital health interventions. Focus groups with African Americans who smoke combustible cigarettes revealed factors impacting the acceptability in using LLM-based interventions to support quit attempts. Efforts to build digital health interventions should prioritize community engagement to reduce apprehensions and improve alignment with community needs and values.
23 May 2026
Read appraisal →PloS one
Audit data governance for disability-inclusive public services: A systematic review and integrative S-A-C framework
This study consolidates interdisciplinary evidence on how audit data governance shapes accountability and service equity in data-intensive public services, with specific sensitivity to disability-inclusive delivery. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, we conducted a protocol-driven systematic literature review of peer-reviewed studies and selected institutional and standards sources published between 2010 and 2025. We searched Scopus and complemented database retrieval with targeted searches of audit, digital government, accessibility, and data-governance portals. We applied a theory-led narrative synthesis to accommodate heterogeneity in designs, domains, and outcome reporting. Synthesizing 125 records, we find that governance effects are produced through three interacting dimensions-service delivery for people with disabilities (S), audit data governance (A), and data-driven culture (C)-that jointly condition transparency, contestability, and distributive impacts. Service delivery arrangements shape where data are generated, which encounters are recorded, and whether access needs, reasonable accommodations, and complaints become organizationally legible. Audit data governance conditions the credibility and usability of audit trails through provenance, metadata, retention, audit logging, and role-appropriate oversight access, shaping both oversight feasibility and privacy risk. Data-driven culture conditions how evidence is interpreted and acted upon, including data literacy, the standing of experiential evidence, and whether audit signals support learning or only compliance. Across the corpus, recurring tensions emerge between optimization and inclusion; transparency and privacy; standardization and reasonable accommodation; automated decisioning and meaningful contestability; and compliance-oriented auditing and learning-oriented governance. Drawing these mechanisms together, we propose an integrative framework linking S, A, and C to explain how auditability and disability inclusion are co-produced across the digital service lifecycle. The framework identifies leverage points for governance reform and evaluation and outlines implications for future empirical testing and for practitioners seeking trustworthy, oversight-ready, inclusive digital public services. A review protocol was prepared before the review; the review was not registered.
23 May 2026
Read appraisal →BMJ open
Australian key stakeholder views regarding implementation of atrial fibrillation screening: a qualitative evaluation
OBJECTIVE: To understand the issues impacting atrial fibrillation (AF) screening and what needs to be considered for a successful national screening programme in Australia. DESIGN: Qualitative design using semistructured interviews and thematic analysis. SETTING: Australian Health. PARTICIPANTS: Six broad stakeholder groups were identified: charities/patient support, healthcare providers, professional bodies, government, research (including Indigenous health) and industry. METHODS: Semistructured interviews were conducted with 25 representative participants. Iterative thematic analysis was used. Coding was driven by the research questions (the current context; is a national screening programme warranted and approaches to a national screening programme) and an inductive approach where novel groupings of information were identified. FINDINGS: The key findings are grouped into four areas. (1) Current opportunistic general practitioner-led screening is ad hoc and fragmented. ISSUES: poor remuneration; lack of health sector collaboration and prioritisation; consumers lack awareness. (2) Systematic screening of all in-scope patients not considered feasible and concerns over lack of evidence. (3) Alternative approaches to increase screening include innovative approaches inside and outside general practice and use of smart technology. (4) Recommendations: (a) Support general practices and address remuneration and workflows; (b) Ensure a clear pathway to treatment; (c) Address data security, management and integration and sensitivity issues with wearable devices; (d) Promote collaboration between key organisations; (e) Address research gaps and (f) Generate culturally appropriate consumer education to promote consumer demand. CONCLUSIONS: Most stakeholders were broadly supportive of AF screening but agreed that current approaches were fragmented and not sufficient. If the forthcoming research evidence supports screening effectiveness on major outcomes, stakeholders envisaged a semi-systematic approach tailored to specific health settings, rather than a formalised systematic national screening programme.
23 May 2026
Read appraisal →PloS one
Enhancing aviation safety: An 80-year data-driven model for classification of aviation incident and accident
The aviation system is safety-critical by nature, and any occurrence of an incident or accident can lead to the loss of human life and significant operational disruptions. The International Civil Aviation Organization (ICAO) emphasizes that every flight must take off and land safely-a goal achieved over 126,000 times daily. Despite major advancements,mishaps and accidents continue to occur, underscoring the need for robust safety management systems. The accurate classification of aviation occurrences (Incident or Accident) reports is essential for safety management, yet manual review is time-consuming and prone to inconsistency. While incident/accident labels are assigned during reporting, automated classification enables rapid triage, detection of potential mislabeling, and support for severity assessment in high-volume aviation safety operations. To address this,we developed and compared three machine learning classifiers-Multinomial Naive Bayes, Random Forest, and Support Vector Machine-using TF-IDF vectorization on an 80-year dataset of 53,770 aviation occurrence summaries obtained from the Transportation Safety Board of Canada. A two-stage evaluation strategy was employed, consisting of an initial 80/20 train-test split to create an independent test set, followed by 5-fold cross-validation applied exclusively to the training data to ensure robustness and prevent optimistic bias. The Support Vector Machine (SVM) classifier achieved the highest classification performance, attaining an accuracy of 98.06% during 5-fold cross-validation, with consistent results across folds, demonstrating its effectiveness in managing high-dimensional textual data and dataset complexity. The proposed framework provides a robust foundation for automated aviation safety report processing, offering practical value for (1) early triage of safety reports, (2) identification of potentially mislabeled cases requiring expert review, and (3) integration into downstream severity assessment pipelines. This work advances beyond prior classification studies by establishing a benchmark on the largest historical aviation safety dataset while delivering a deployable and operationally relevant framework for real-world safety management applications. The findings offer valuable insights for regulatory authorities and airline operators, contributing to enhanced safety oversight, improved response strategies, and safer aviation operations.
23 May 2026
Read appraisal →Systematic reviews
Impact of the COVID-19 pandemic on diagnosis, and healthcare utilization, among patients with cancer (lung, breast, and pancreas) and cardiovascular diseases (HF, AF, hypertensive, and chronic ischemic heart disease) in Germany: two systematic reviews.
BACKGROUND: The COVID-19 pandemic and related non-pharmaceutical interventions (NPIs) (e.g., lockdowns and contact restrictions) disrupted routine healthcare delivery. In Germany, these measures affected diagnostic and treatment services for people with cancer and cardiovascular diseases, potentially delaying diagnosis and adversely influencing outcomes. We assessed whether and to what extent diagnosis, health utilization and health outcome among patients with selected cancer and cardiovascular conditions changed in Germany during the pandemic. METHODS: We conducted two systematic reviews of studies from Germany on selected cancers (breast, lung and pancreatic) and cardiovascular conditions (atrial fibrillation/flutter, heart failure, hypertensive and chronic ischemic heart disease). Protocols were registered in PROSPERO and the reviews were reported in accordance with PRISMA. We searched PubMed, Web of Science, Cochrane Library, Scopus, and Embase and screened grey literature. Outcomes included changes in new diagnoses, healthcare utilization, treatment, and disease-specific mortality during the pandemic (2020-2023) compared with the pre-pandemic period (2018-2019). Two reviewers independently screened records, extracted data, and assessed risk of bias using an adapted ROBINS-E tool. Owing to heterogeneity, we synthesized findings narratively. RESULTS: We screened 1991 records for cancer and 4,981 records for cardiovascular diseases, and included 9 cancer studies and 10 cardiovascular studies. For cancer, several studies reported a relative reduction in new breast and lung cancer diagnoses of up to 25% during lockdown periods; hospital admissions decreased by up to 9%. For cardiovascular conditions, hospital admissions for atrial fibrillation/flutter and heart failure decreased by up to 20%, particularly during pandemic peaks. Evidence on treatment delays, changes in treatment, and mortality was limited, and outcomes for other included diagnoses were often not reported. DISCUSSION: The available evidence indicates substantial reductions in hospital admissions and new diagnoses among patients with cancer and cardiovascular disease in Germany during the pandemic, suggesting major disruptions to care delivery. However, heterogeneity and gaps in the evidence base limit a comprehensive assessment of downstream outcomes. More comprehensive, linked data and further research are needed to quantify the full pandemic's impact and to strengthen health-system resilience for future crises.
23 May 2026
Read appraisal →Current environmental health reports
Industrial Pollution and Health in Louisiana: A Systematic Review of Quantitative and Qualitative Studies
PURPOSE OF REVIEW: Louisiana has one of the largest concentrations of petrochemical industry in the USA. Many studies have assessed patterns of industrial pollution and health in Louisiana; we aim to systematically review this evidence. We systematically searched PubMed, Web of Science, Embase, APA PsycInfo, and GreenFILE for peer-reviewed papers published 1999-2024 that reported geographical variation in health or industrial pollution, and/or tested for an association between the two in Louisiana. We used Covidence to support standardized review and extraction. RECENT FINDINGS: We identified 2485 non-duplicate papers in our search; 53 met the inclusion criteria. Most reported quantitative findings. All studies of industrial pollution described air pollution (some also described other pollution). Studies described various health outcomes, including cancer, respiratory health, mortality, and COVID-19. Overall, people who lived closer to industrial activity had higher pollution exposure and worse health. Black and lower-income residents were exposed to more industrial activity than white and higher-income residents. Twenty-one studies assessed statistical associations between industrial pollution and health; many found an association. Twenty-one studies were quantitative and adjusted for confounding, 29 studies did not adjust for confounding (including qualitative studies), and three studies did not adjust for confounding and had authors with industry ties. Evidence suggests that there is a higher burden of air pollution and worse health outcomes in industrialized areas of Louisiana. While there was some evidence of significant associations between industrial pollution and health outcomes, research with larger sample sizes and improved pollution exposure measurements could be informative.
23 May 2026
Read appraisal →BMJ open
Impact of COVID-19-related data drift on machine-learning prognostic models predicting 30-day opioid-related emergency department visits, hospitalisation or mortality: a population-level administrative data study in Alberta, Canada
OBJECTIVE: To develop machine-learning (ML) models during the COVID-19 pandemic and adjacent time periods to evaluate the impact of data drift on model performance. DESIGN: This prognostic study used population-level administrative health data to develop ML prediction models. SETTING: Alberta, Canada during 2019-2023. PARTICIPANTS: All patients over 18 who received at least one opioid dispensation from a community pharmacy within the province of Alberta between 2019-2023. EXPOSURE: Each opioid dispensation served as the unit-of-analysis. MAIN OUTCOMES/MEASURES: Opioid-related outcomes were identified from linked health administrative datasets. Light Gradient Boosting-machine models were developed on pre-pandemic, pandemic and endemic data and temporally validated on 2023 data (pre-pandemic model was also validated on 2020-2021 data) to predict the risk of emergency department visit, hospitalisation or mortality within 30-days of an opioid dispensation. We described key feature distributions across the study time period and changes in model prediction performance on the validation sets using relevant metrics. RESULTS: Among 1.2 million study participants representing over 13 million opioid dispensations, there were 59 809 (2.1%), 134 402 (2.4%) and 62 143 (2.3%) events reported in the pre-pandemic (2019), pandemic (2020 and 2021) and endemic (2022) time periods, respectively (estimated 2023 validation set pre-test probability of 2.8%). Notable differences in key features were observed in the 2020-2021 model relative to other years. In the 2023 validation set, discrimination performance was highest for the pre-pandemic and endemic models compared with the pandemic model (0.81, 0.83, 0.74, respectively). A similar trend regarding changes from pre-test to post-test probabilities in higher categories of predicted risk (23%, 40%, 16%) was observed. 2020-2021 had the lowest discrimination performance (0.71) and uninformative post-test probabilities (<10%). CONCLUSION: COVID-19 pandemic health data contributed to significant ML drift. Although ML approaches allow for quick re-training to mitigate drift, health regulators should approach ML prediction with caution when using pandemic-times data.
23 May 2026
Read appraisal →JMIR research protocols
A Large, Diverse, Urban Cardiovascular Health e-Cohort in Childhood and Adolescence: Protocol for the Young Hearts Study
BACKGROUND: Cardiovascular health (CVH), defined as a composite of 8 health factors and behaviors ranging from body composition to sleep duration, is strongly associated with the risk for future cardiovascular events in adults. However, there is little data on CVH among contemporary, diverse cohorts of children and adolescents. OBJECTIVE: This protocol describes the completed recruitment of a diverse pediatric e-cohort based in Chicago. We include details about ongoing longitudinal data collection for CVH behaviors, as well as neighborhood and environment-based socioeconomic factors, and linkage to electronic health records (EHRs) for direct capture of CVH factors. METHODS: Young Hearts (YH) uses a longitudinal cohort design, linking participant responses to annual electronic surveys to EHRs. Parents/guardians of children aged 0-17 years and adolescents aged 18 years are asked to complete surveys at 3 e-visits, completed annually in consecutive years. Adolescents aged 12-17 years are invited to complete surveys at each e-visit to provide self-reports of their data in addition to their parents/guardians. As adolescents reach the age of majority, they re-consent and complete their remaining e-visit data. Participants' clinical data are abstracted from EHRs at 6 health systems in Chicago and linked to their survey data. The main study outcome is the CVH score, adapted from the Life's Essential Eight framework for use in pediatric populations. We will also study component CVH behaviors and factors, each assessed using developmentally-appropriate measures, including body mass index, blood pressure, lipids, glycemic control, diet, physical activity, sleep, and smoking exposure. Our innovative study design will allow us to model trajectories of pediatric CVH from birth through 20 years of age. Funding for this study was provided by the National Heart, Lung, and Blood Institute (R01HL155864). RESULTS: The YH study, funded in March 2021, recruited, enrolled, and consented 7114 children and adolescents aged 0-18 years between April 2022 and February 2025. Baseline surveys have been completed by 6651 participants, of whom 3259 (49%) were female, and the mean age was 7.4 (SD 5.4) years. Data collection is still in progress, with completion anticipated in February 2027. We aim to publish results beginning in 2026. CONCLUSIONS: This study will define the epidemiology of cardiovascular risk factors in a diverse, contemporary cohort of US children and adolescents and identify behavioral and structural individual- and area-level economic, psychosocial, and lifestyle factors associated with identified disparities. We anticipate that the YH cohort will become an ongoing resource for pediatric CVH research.
23 May 2026
Read appraisal →BMJ paediatrics open
Enhancing respiratory virus surveillance among hospitalised children: a machine learning-based predictive model.
BACKGROUND: Viral respiratory tract infections (vRTIs) are a leading cause of paediatric hospitalisation and healthcare utilisation. Existing syndromic surveillance tools, including the WHO Severe Acute Respiratory Infection definition, demonstrate limited diagnostic accuracy in children whose symptom profiles vary widely. This study aimed to develop a machine learning (ML) model to predict microbiologically confirmed vRTIs in hospitalised children and to evaluate performance across age groups and viral pathogens. METHODS: We conducted a retrospective cross-sectional study of 2050 paediatric patients (<18 years) admitted with acute respiratory infections to two tertiary paediatric hospitals in Canada. Predictors included age, sex, hospital transfer status, chronic comorbidity status and 22 presenting symptoms. The primary outcome was microbiologically confirmed vRTI, determined by multiplex PCR or rapid antigen testing. Six ML algorithms were trained and the best-performing model, identified by area under the receiver operating characteristic curve (auROC), was tested on age subgroups, viral pathogens and sites. RESULTS: Among 2050 patients (median (IQR) age 2.4 (0.8-5.2) years), 1831 (89.3%) tested positive, most commonly for respiratory syncytial virus (RSV) (38.7%) and enterovirus/rhinovirus (32.8%). Logistic regression with L2 regularisation demonstrated the best performance (auROC, 0.754; 95% CI 0.697 to 0.808; sensitivity, 69.2%; specificity, 69.9%), with greatest performance among children <1 year (auROC, 0.763) and RSV cases (auROC, 0.727). CONCLUSIONS: An ML-based logistic regression model using admission data accurately predicted paediatric vRTIs, outperforming traditional syndromic surveillance definitions, especially among infants <1 year. By integrating ML models into hospital electronic medical records, healthcare systems can achieve enhanced respiratory virus surveillance, faster outbreak detection, greater diagnostic efficiency and improved pandemic preparedness.
23 May 2026
Read appraisal →Reproduction & fertility
Patient characteristics and lifestyle determinants of quality of life among women with endometriosis: a systematic review
ABSTRACT: Endometriosis is a chronic inflammatory disease presenting with debilitating symptoms strongly impacting patients' quality of life (QoL). Assessing QoL is crucial for understanding the full patient experience beyond clinical symptoms. This narrative systematic review specifically aimed to identify and describe non-pharmacological and non-surgical factors associated with QoL in women with endometriosis as reported in the literature. Following PRISMA guidelines, we systematically searched PubMed, MEDLINE, Web of Science, and Embase up to January 15, 2025, for case-control, cohort, randomized controlled trials, and cross-sectional studies. This study was registered in PROSPERO (registration number: CRD42023438457) Eligible studies assessed socio-demographic characteristics, lifestyle factors, symptoms, comorbidities, or coping strategies in relation to QoL among women with endometriosis. Twenty-one studies with a low risk of bias were included. A better QoL was related to favorable socioeconomic profiles (n = 3), high care satisfaction (n = 2), partner involvement (n = 1), healthier lifestyle habits (n = 1), and the use of coping therapeutic strategies. Poor QoL was associated with poor health (n = 5), more severe symptoms (n = 5), unhealthy lifestyle habits (n = 2), and ineffective use of coping strategies (n = 2). This review highlights a broad range of non-medical determinants of QoL, underscoring that clinical measures alone fail to capture the full patient experience. By consolidating evidence across diverse study designs, it offers a comprehensive overview of modifiable factors that could inform holistic, patient-centered approaches to endometriosis care. Further prospective and interventional studies are needed to clarify causal pathways and evaluate the effectiveness of targeted strategies to improve QoL. LAY SUMMARY: Endometriosis is a chronic disease affecting around 10% of women of reproductive age, associated with pain, infertility, and significant impacts on daily life. Because clinical measures alone fail to capture the full patient experience, assessing QoL is essential to understand the real burden of the disease. This review examined non-pharmacological and non-surgical factors that may be associated with QoL, such as lifestyle habits, socioeconomic conditions, health status, and coping strategies. Across 21 studies, we found that a better QoL was linked to good healthcare access, healthy habits, and effective coping mechanisms. Conversely, severe symptoms, poor health, and unhealthy lifestyles (smoking and alcohol use) were associated with worse QoL. The findings highlight the need for a more holistic approach to endometriosis care, combining psychological support, lifestyle guidance, and improved access to quality healthcare. Future research should use standardized QoL tools and robust study designs to develop evidence-based strategies that can meaningfully enhance patient well-being.
23 May 2026
Read appraisal →Occupational and environmental medicine
Lymphoid neoplasms and benzene exposure using a revised classification scheme: systematic review and meta-analysis
Lymphoid neoplasms are a diverse group of cancers derived from lymphocytes, with classification recently updated by the 5th edition of the WHO Classification of Haematolymphoid Tumours (WHO-HAEM5). Benzene, a well-known carcinogen, is widely used in industries and environmental exposures vary; however, its association with specific lymphoid neoplasm subtypes remains unclear due to historical classification challenges. This study aimed to clarify the risk of lymphoid neoplasms related to benzene exposure using the updated WHO-HAEM5 framework.A systematic review and meta-analysis were conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eligible studies were comparative human studies evaluating benzene exposure and lymphoid neoplasm risk, with sufficient data for risk estimates. Inclusion criteria specified study designs, participants, exposures and outcomes based on clinical diagnoses. Data were independently extracted by multiple reviewers. The main outcome was risk of lymphoid neoplasms and subtypes analysed by random-effects meta-analysis with heterogeneity and bias assessments.From 1488 records, 95 studies met criteria (65 occupational and 30 environmental exposure). Benzene exposure significantly increased overall lymphoid neoplasm risk (RR 1.26; 95% CI 1.18 to 1.35). B-cell neoplasms showed elevated risk (RR 1.26; 95% CI 1.16 to 1.37), including mature B-cell neoplasms, Hodgkin lymphoma and plasma cell neoplasms. T-cell and natural killer cell neoplasm risk was not significantly increased overall. Occupational exposures conferred higher risks with lower heterogeneity than environmental exposures.Benzene exposure is strongly associated with increased risk of lymphoid neoplasms, particularly B-cell subtypes, supported by the refined WHO-HAEM5 classification reducing heterogeneity. This study underscores the importance of biologically informed disease classification and the need for targeted occupational safety and environmental health policies.The review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (Registration ID: CRD420251063844) .
23 May 2026
Read appraisal →Journal of medical Internet research
Effect of Integrated Internet-Based Acceptance and Commitment Therapy and Behavioral Activation Among Ethnic Minority Young Adults With Alcohol Use Disorder in Hong Kong: Pilot Randomized Controlled Trial
BACKGROUND: Alcohol use disorder (AUD) profoundly affected ethnic minority young adults due to unique stressors, such as acculturation challenges and discrimination. Our prior studies found that experiential avoidance behavior and discrimination significantly contributed to AUD. These findings warranted third-wave interventions, such as acceptance and commitment therapy (ACT). Nonetheless, barriers to engagement with value-based activities may affect ACT efficacy. Behavioral activation (BA) may be an alternative for this shortcoming. Integrating these interventions has shown promise. However, no studies evaluated its effectiveness in this group. Therefore, evaluating the preliminary effectiveness and feasibility of this intervention was needed. OBJECTIVE: This study aimed to evaluate the feasibility measures. The secondary objective aimed to examine its effectiveness on cumulative abstinence duration, drinking days, drinks per drinking day, heavy drinking days, alcohol abstinence self-efficacy, readiness to change, psychological flexibility (Acceptance and Action Questionnaire-version II), and everyday discrimination score. METHODS: A pilot parallel randomized controlled trial was conducted. Forty young ethnic minorities who can speak English and have AUD based on DSM-5 (Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition]) criteria were recruited and randomly assigned to either Acceptance and Commitment Therapy with Behavioral Activation (ACT-BA; n=20) or Treatment-as-Usual (TAU; n=20) using a computer-generated random number; assessors were blinded to group assignment. Outcomes were collected at baseline (T0) and postintervention (T1). The analysis included descriptive statistics, independent samples t test, chi-square test, and generalized estimating equations with multiple imputations. To further supplement findings, a qualitative interview was conducted. RESULTS: A total of 148 ethnic minority young adults were screened, with an eligibility rate of 38.5% (57/148). Of these, 85.9% (49/57) consented, and among them, 81.6% (40/49) were randomized to either the ACT-BA or TAU. The retention rate was 82.5% (33/40), of which 75% (30/40) completed the postintervention assessment (ACT-BA: 16/20, 80%; TAU: 14/20, 70%). The adherence rate was 81.7% (4.9/6 sessions), and participants reported no adverse effects. Finally, 40 participants (20 for each group) were analyzed. The intervention group showed a promising improvement in drinking days (B=-4.12, 95% CI -8.10 to -0.13; P=.04, d=-0.57), drinks per drinking day (B=-1.56, 95% CI -3.06 to -0.07; P=.04, d=-1.89), alcohol abstinence self-efficacy (B=11.95, 95% CI 0.10-23.81; P=.048, d=0.81), and Acceptance and Action Questionnaire-version II (B=-6.41, 95% CI -12.77 to -0.06; P=.04, d=-0.65). CONCLUSIONS: This study, unlike existing evidence, presents an innovative integration of ACT and BA delivered via an internet-based self-help format. The findings contribute to the field by providing preliminary evidence that this integrated intervention is feasible and promising for AUD. The main implication in the real world is to conduct a fully powered randomized controlled trial to further examine its effectiveness with longer follow-up to serve as a stand-alone treatment option for ethnic minorities.
22 May 2026
Read appraisal →PloS one
A collaborative approach to applying Natural Language Processing (NLP) to Domestic Homicide Reviews (DHRs): A study protocol
Since 2011, there has been a statutory requirement in England and Wales to conduct a Domestic Homicide Review (DHR) into any domestic abuse-related death: a multi-agency review into the death of a person aged 16 or over that appears resulting from violence, abuse or neglect from an intimate partner, family member or household member. However, analyses of large numbers of DHRs are rare. One of the core challenges is the time and effort required to analyse narrative text within reports. Doing so manually is both time-consuming and resource-intensive and is a primary reason why researchers typically focus on only a portion of the available data. Natural Language Processing (NLP)-a sub-branch of artificial intelligence that enables computers to interpret and process natural language-provides a viable and scalable alternative by offsetting much of the heavy data processing to a computer. This protocol outlines a study to assess the feasibility of applying NLP to DHRs. The study will take a collaborative approach which balances the speed and scale of automation with the embedded knowledge and expertise of practitioners. This approach helps to ensure that outputs of NLP are sensitive and transparent about the biases common within datasets on violence and abuse. Based on initial consultations, we identify the priority research questions for investigation. In addition, we outline details of an ongoing collaboration with one partner, Imkaan. The protocol describes the data access, and retrieval and analysis stages before summarising how feasibility will be evaluated. We anticipate that several challenges will emerge within this study and identify strategies for mitigation. We suggest that working with practitioners who hold deep contextual knowledge about the social realities of violence and abuse, including language, risks, and experiences, mean that tools can be developed that are accountable to communities and appropriately applied to real-world problems.
22 May 2026
Read appraisal →Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Safety and Immunogenicity of a Fourth Dose of Omicron BA.1-Adapted BNT162b2 COVID-19 Vaccines in Adults 18-55 Years Old
BACKGROUND: Emergence of severe acute respiratory syndrome coronavirus 2 sublineages warrants the use of sequence-adapted vaccines to provide protection against coronavirus disease 2019. METHODS: In this phase 3 trial, adults 18‒55 years old who had previously received three 30 μg doses of BNT162b2 vaccine were randomized to receive a 60 or 30 μg dose of bivalent Omicron BA.1‒adapted BNT162b2 comprising equal amounts of ancestral and monovalent messenger RNA BA.1 (bivalent BA.1) or a 60 μg dose of monovalent Omicron BA.1‒adapted BNT162b2 (monovalent BA.1). Safety (local reactions, systemic events, adverse events [AEs], and serious AEs) was the primary objective. Exploratory analyses assessed immune responses against Omicron BA.1, BA.4, and BA.5 subvariants and ancestral strain. RESULTS: Among the 1054 randomized participants who received monovalent BA.1 or bivalent BA.1, frequencies of local reactions, systemic events, and AEs were slightly higher with 60 µg monovalent BA.1 than either bivalent BA.1 dose level. One month after vaccination, bivalent BA.1 (30 and 60 μg) and monovalent BA.1 (60 μg) induced substantial neutralizing responses against Omicron BA.1 (50% neutralizing titer geometric mean fold rises [GMFRs], 15.4 [95% CI 12.4-19.2], 17.1 [13.7-21.4], and 24.6 [19.3-31.4], respectively) and ancestral strain (GMFRs, 6.2 [5.1-7.6], 7.3 [6.0-8.9], and 7.0 [5.7-8.7], respectively). In a smaller (n = 30/treatment arm) sentinel cohort, all study vaccines modestly neutralized Omicron BA.4 and BA.5. CONCLUSIONS: Bivalent and monovalent BA.1‒adapted vaccines had a safety profile similar to the original BNT162b2 30 μg and induced substantial neutralizing responses against Omicron BA.1 and ancestral strains. CLINICAL TRIALS REGISTRATION: NCT04955626.
22 May 2026
Read appraisal →BMJ open
Patient preferences and willingness-to-pay for AI-enabled blended type 2 diabetes care by digital experience and socioeconomic status: a discrete-choice experiment in China
OBJECTIVES: To elicit stated preferences and willingness-to-pay (WTP) for artificial intelligence (AI)-enabled blended care in type 2 diabetes mellitus (T2DM), and to examine preference heterogeneity by digital experience and socioeconomic status (SES). DESIGN: Cross-sectional discrete choice experiment (DCE). SETTING: 12 community health centres in Jiaozuo and Puyang, Henan Province, China. Data were collected between June and August 2025. PARTICIPANTS: 423 adults diagnosed with T2DM for at least 6 months, recruited using consecutive convenience sampling from routine follow-up appointments. Of 769 participants who completed the survey, 346 were excluded following prespecified data quality criteria (retention rate: 55.0%). OUTCOME MEASURES: Outcome measures included preference weights and WTP (in Chinese Yuan, ¥) for five DCE attributes: monthly subscription fee, recommendation source, feedback modality, in-person follow-up frequency and expert oversight, estimated using mixed logit models. Simulated uptake probabilities for tailored service packages across four user profiles were computed. RESULTS: Among 423 participants, 80.6% had never used AI tools. Price was the dominant driver of choice (62.7% relative attribute importance). Profound preference heterogeneity emerged across subgroups: rural residents (n=78) were highly price-sensitive but preferred physician endorsement (WTP ¥17.58 (US$2.55), 95% CI ¥5.98 to ¥29.17); female participants (n=224) valued guideline recommendations (WTP ¥18.45 (US$2.67), 95% CI ¥7.81 to ¥29.40); and diabetes app users (n=34) were the least price-sensitive but showed a negative preference for AI instant feedback, instead preferring human dietitian feedback. Expert oversight carried a consistent negative WTP across all profiles. Targeting tailored service bundles to intended subgroups increased uptake by 8-16 percentage points compared with non-targeted bundles. CONCLUSIONS: A 'digital experience paradox' exists whereby digitally experienced users view human interaction as a premium service, while underserved groups rely on specific trust markers such as physician endorsement. To avoid widening the digital divide, AI-enabled blended diabetes care must move beyond standardised models towards configurable, equity-driven service pathways.
22 May 2026
Read appraisal →Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Evaluating Personal and Environmental Decolonization Strategies for Children With Skin and Soft Tissue Infection and Their Households - A Randomized Clinical Trial
BACKGROUND: Staphylococcus aureus colonization predisposes to skin and soft tissue infection (SSTI). Given the waning effectiveness of decolonization, we evaluated periodic-personal decolonization and household environmental decontamination to reduce SSTIs among households affected by S. aureus. METHODS: Households of children with community-associated S. aureus SSTI participated in an open-label randomized trial. After baseline decolonization, households were randomized 1:1:1 to a 3-month decolonization intervention: (1) periodic-personal (twice weekly chlorhexidine bathing and monthly intranasal mupirocin application); (2) environmental-hygiene (weekly household surface disinfection and enhanced laundry measures); or (3) integrated-approach of both periodic-personal and environmental-hygiene. Over 9 months, participants and household surfaces were sampled at 5 study visits to detect S. aureus; SSTI incidence was recorded. The primary outcome was household-level cumulative SSTI at 3 months, comparing the integrated-approach to the combined personal-periodic and environmental-hygiene groups. RESULTS: Between 2015 and 2021, 196 index patients and their household contacts (n = 623) were enrolled. Cumulative SSTI incidence did not differ between groups during the 3-month intervention. In index patients and household contacts with SSTI in the year prior to enrollment, SSTI incidence was lower among the integrated-approach at 6- and 9-months compared to the combined periodic-personal and environmental-hygiene groups. In multivariable analyses, prior year SSTI was associated with subsequent SSTI; intervention group was not significant. All interventions reduced methicillin-resistant S. aureus, but not methicillin-susceptible S. aureus, personal colonization over 9 months. CONCLUSIONS: While an integrated-approach of prolonged personal and environmental decolonization reduced SSTIs among participants with prior year SSTI, prior SSTI strongly predicted SSTI incidence longitudinally. Novel prevention strategies are needed.
22 May 2026
Read appraisal →BMJ open respiratory research
Symptom-based rehabilitation in people with post-COVID-19 condition (RELOAD study): a randomised controlled trial
RATIONALE: Post-COVID condition (PCC) is characterised by persistent symptoms that impair health-related quality of life (HRQoL); rehabilitation (REHAB) strategies remain scarce. OBJECTIVE: To investigate the effect of a symptom-based REHAB programme versus usual care on HRQoL in people with PCC. METHODS: In this single-blind randomised controlled trial, a total of 132 people with PCC were randomised to either a REHAB group or a control group, with 104 completing the trial. The REHAB group received a multimodal 3-week REHAB programme tailored to the participant's primary symptom-based group (fatigue, cognitive problems or somatic symptoms); the control group received usual care. The primary endpoint was the between-group difference in change in HRQoL, measured by the 12-item Short Form Health Survey (SF-12) physical component summary (PCS) score at 3 weeks post baseline (intervention period). Changes from baseline to a 3-month follow-up after the intervention period were also analysed as a secondary measure. Additional outcomes included mental HRQoL (SF-12 mental component summary (MCS)), depression symptoms (Patient Health Questionnaire 9 (PHQ-9)) and anxiety symptoms (Generalized Anxiety Disorder 7 (GAD-7)). RESULTS: Participants (mean age 47±12.3 years, 90.4% not hospitalised during acute SARS-CoV-2 infection, 69.2% female) in the REHAB group (n=47) showed a significantly greater improvement in PCS compared with the control group (n=57) (mean difference (Δ) 2.9 points, 95% CI 0.2 to 5.7, p=0.038) at 3 weeks post baseline. This difference remained significant at the 3-month follow-up (Δ 4.2 points, 95% CI 1.5 to 6.9, p=0.003). The REHAB group also showed significant improvements in mental HRQoL (MCS: Δ 5.7 points, 95% CI 2.0 to 9.4, p=0.003), as well as in depression symptoms (PHQ-9: Δ -2.7 points, 95% CI -4.2 to -1.2, p<0.001) and anxiety symptoms (GAD-7: Δ -2.4 points, 95% CI -3.7 to -1.1, p<0.001) at 3 weeks post baseline compared with the control group. At the 3-month follow-up, the reduction in depression symptoms remained significant, while no significant differences were observed for mental HRQoL or anxiety symptoms. CONCLUSION: A symptom-based rehabilitation programme significantly improved HRQoL in individuals with PCC after 3 weeks, with some benefits persisting at 3 months. TRIAL REGISTRATION NUMBER: NCT05172206.
22 May 2026
Read appraisal →Psychological medicine
Global prevalence of prolonged grief disorder during the COVID-19 pandemic under standardized diagnostic frameworks: A systematic review and meta-analysis
Prolonged grief disorder (PGD), recently classified in ICD-11 and DSM-5-TR, is characterized by persistent and functionally impairing grief lasting beyond 6-12 months. The COVID-19 pandemic was accompanied by widespread mortality, social isolation, disrupted mourning rituals, and social disconnection, raising concerns about a potentially high burden of PGD during the pandemic period. We conducted a systematic review and meta-analysis, following PRISMA guidelines and PROSPERO registration (CRD42023463720), to estimate PGD prevalence under standardized ICD-11 and DSM-5-TR diagnostic frameworks and to examine potential moderators during the COVID-19 pandemic. PubMed, EMBASE, and the Cochrane Library were searched from inception to October 2024. Eligible studies included adults who experienced bereavement during the pandemic and were assessed using validated PGD instruments (PG-13-R, ICG, BGQ). Random-effects models were applied to pool prevalence estimates, with subgroup and meta-regression analyses. Thirteen studies comprising 5,766 participants were included. The pooled prevalence of PGD during the pandemic period was 24% (95% CI: 13%-36%), with the highest estimates observed in China (43%, 95% CI: 33%-54%). In the overall pooled analysis, studies applying DSM-5-TR criteria yielded lower prevalence estimates than those using ICD-11 criteria (18% vs.26%, p = 0.41). Digital interventions showed no statistically significant pooled effects (Hedges' g = -0.38, 95% CI: -0.90 to 0.14). The high and geographically heterogeneous prevalence of PGD observed during the COVID-19 pandemic underscores the need to strengthen mental health surveillance, standardized assessment, and service accessibility in large-scale public health emergencies, and provides important evidence to inform population-level interventions and resource allocation strategies.
22 May 2026
Read appraisal →Journal of medical Internet research
Receipt of Medicines Information From the Internet and Other Information Sources Among Adult Medicine Users in Developed Economies, 2010-2025: Systematic Review
BACKGROUND: The internet, social media, and digital health tools have transformed access and receipt of medicines information (MI), complementing or replacing traditional sources, such as physicians, pharmacists, and package leaflets. OBJECTIVE: This study aimed to examine the prevalence and patterns of adult medicine users' receipt of MI from electronic sources (eg, internet and social media) compared with traditional sources, and to assess trends in the receipt of MI in developed economies since 2010. METHODS: A systematic search was conducted in CINAHL, the Cochrane Library, ProQuest, Scopus (including Embase and MEDLINE), and Web of Science databases for peer-reviewed studies conducted and published between January 1, 2010, and December 31, 2025. Studies including adults (≥18 years) in developed economies were eligible. The review followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Methodological quality and risk of bias were assessed using the Mixed Methods Appraisal Tool. Due to substantial heterogeneity, findings were synthesized narratively without meta-analysis. RESULTS: Twenty-six studies from 10 countries, involving 19,891 medicine users, were included. Most studies were cross-sectional surveys (n=19), with only one being a national long-term trend study. Physicians, pharmacists, and package leaflets consistently remained the most common MI sources, irrespective of patient group, country, or study design. No clear temporal trends in MI receipt were observed. Variations in the frequency of MI receipt were evident across research methods, medicine user groups, and types of medicines. Individuals with greater familiarity with the internet were more likely to receive MI from electronic sources, such as websites and social media. In most studies, MI obtained from social media was not distinguished from other internet-based sources. Half of the studies focused on heterogeneous medicine user groups (n=14), while the remainder examined specific medicine user groups (n=12). Although the methodological quality of the studies was generally acceptable, only 3 studies reported the use of an explicit theoretical framework. CONCLUSIONS: Traditional MI sources remain central for adult medicine users despite the growing role of electronic platforms. While the receipt of MI from electronic sources appears more common among internet-experienced users, no significant temporal trends in using these sources were identified. Further research is needed to better distinguish between different digital MI sources, including artificial intelligence-based MI sources, and to explore their evolving roles, implications for health-related decision-making, and associations with user characteristics and health contexts in the digital era. This review is innovative in systematically comparing traditional and electronic MI sources across developed economies and in highlighting methodological and conceptual gaps in existing research. By synthesizing cross-national evidence and identifying the need for clearer differentiation of digital MI subtypes, the study contributes to the field and informs the development of more targeted, reliable, and user-centered MI strategies in real-world health care settings.
22 May 2026
Read appraisal →BMJ (Clinical research ed.)
Calcium, vitamin D, or combined supplementation to prevent fractures and falls: systematic review and meta-analysis
OBJECTIVE: To assess the effect of calcium, vitamin D, or combined supplementation on fractures and falls in adults. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Trials included in systematic reviews from 2014, three databases (Medline, Embase, CENTRAL) to 19 February 2025, clinical trial registries, abstracts from scientific meetings, and references from included studies. ELIGIBILITY CRITERIA: Randomised controlled trials comparing calcium, vitamin D, or combined supplementation with placebo or no treatment in adults (≥18 years) not receiving drug treatment for osteoporosis. DATA EXTRACTION AND SYNTHESIS: The primary outcome was the risk of any fracture. Secondary outcomes included the risk of hip fracture, non-vertebral fracture, vertebral fracture, and falling, as well as the total number of falls. Pairs of reviewers independently screened trials, extracted data, and assessed risk of bias using the second version of Cochrane's risk of bias tool. Findings were synthesised using random effects meta-analyses and appraised using Grading of Recommendations Assessment, Development and Evaluation, with application of thresholds for absolute effects considered important. RESULTS: This review included 69 trials involving 153 902 participants. Participants in most of the trials were community dwelling (87%) and not at high risk of fractures or falls (73%). For the primary outcome of any fracture, little to no effect was found from use of calcium supplements (11 trials, 9067 participants; risk ratio 0.91, 95% confidence interval 0.81 to 1.01; moderate certainty), vitamin D supplements (36 trials, 92 045 participants; 1.00, 0.95 to 1.06; high certainty), or combined supplementation (15 trials, 51 126 participants; 0.91, 0.84 to 0.99; high certainty). Calcium, vitamin D, or combined supplementation appeared to have little to no effect on other fracture and fall outcomes, based largely on moderate to high certainty of evidence. The findings remained robust after an extensive exploration of heterogeneity across multiple subgroup analyses. Evidence for high risk patients or those requiring residential care was limited for many outcomes for calcium monotherapy and for combined supplementation. CONCLUSION: Based on absolute risk reductions and thresholds considered clinically meaningful, this review found little to no benefits from use of calcium, vitamin D, or combined supplementation on the prevention of fractures and falls. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42023483915.
22 May 2026
Read appraisal →BMJ military health
Risk and protective factors for suicide-related outcomes among serving military personnel: a systematic review of cohort studies
INTRODUCTION: Understanding risk and protective factors for suicide-related outcomes (suicidal ideation, attempts, and deaths) among military personnel is key to the development and design of suicide prevention initiatives. Current literature has predominantly focused on ex-serving or a combination of ex-personnel and serving-personnel. Therefore, factors that may be pertinent for serving personnel are less understood. This review aims to identify risk and protective factors for suicide-related outcomes comprising serving military personnel. METHODS: The review adhered to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and was registered on PROSPERO. A systematic literature search of academic databases on military personnel and suicide from 2004 was conducted. Two independent reviewers conducted study selection. Inclusion criteria included serving personnel, cohort study design, and suicide-related outcomes. Exclusion criteria were National Guard or reservists, and studies not in English. Data on study and participant characteristics, military-specific variables, and suicide-related outcomes were extracted. All studies were critically appraised. RESULTS: A total of 53 studies were included. Most studies were published in the past 10 years, comprised army personnel from the USA, and focused on suicide attempts. Overarching risk factor categories included adverse military experiences, deployment, repeated help seeking and support, junior rank, occupation and time in service and vulnerability factors within the military context. Since many of these risk factors are inherent to military service, they may potentially be considered non-modifiable. Despite a limited number of studies on protective factors, several studies found that unit cohesion reduced the likelihood of suicidal ideation and suicide attempts. CONCLUSIONS: Suicide prevention strategies within the military may be enhanced by targeting risk factors that are potentially modifiable. Less modifiable risk factors could potentially be targeted through improved personnel management practices, particularly in preparation for and after deployment among first-year personnel. Longitudinal research programmes that identify and examine risk and protective factors for serving military personnel are needed. PROSPERO REGISTRATION NUMBER: CRD42024558183.
22 May 2026
Read appraisal →The British journal of ophthalmology
Impact of artificial intelligence on the availability, accessibility, acceptability and quality of ophthalmic disease screening services: a scoping review
This scoping review examines the existing literature on the application of artificial intelligence (AI) in screening for eye diseases, with a focus on evaluating whether AI-assisted diagnostic technologies enhance the availability, accessibility, acceptability and quality of screening services. 42 original studies were selected for in-depth analysis, including those employing health economic evaluations. Methodological quality was assessed using the Mixed Methods Appraisal Tool, with the majority of studies demonstrating high quality-24 scored 5/5, 15 scored 4/5 and the rest scored 3/5. Among the included studies, 34 compared manual screening with either AI-assisted or fully AI-driven approaches. Availability was the most frequently studied aspect (28 studies), followed by acceptability (12 studies), whereas accessibility and service quality were less commonly addressed. Overall, AI shows significant potential to improve the cost-effectiveness of eye care services and enhance patient access, particularly in remote or underserved regions. It was also well-accepted by patients, with high satisfaction and improved referral compliance. The findings suggest that AI holds promise for advancing eye disease screening, although large-scale, long-term trials are needed to effectively integrate AI into the reconstruction of screening processes and the reshaping of eye health service systems.
22 May 2026
Read appraisal →JMIR mental health
Efficacy of a World Health Organization-Guided Self-Help Intervention for Reducing Psychological Distress in Afghan Refugees: Randomized Controlled Trial
BACKGROUND: Common mental health disorders are highly prevalent among refugees. There is an urgent need to address the mental health burden in this population. OBJECTIVE: This study tested the efficacy of an individually supported self-help stress-management intervention developed by the World Health Organization-Doing What Matters in Times of Stress (DWM)-in reducing psychological distress and improving functioning among refugees in Indonesia, a major transit country in the Asia-Pacific region. METHODS: A single-blind randomized controlled trial with 303 Farsi-speaking refugees was conducted between June 2024 and June 2025. Participants with moderate to high psychological distress (Kessler Psychological Distress Scale [K10] score≥20) were randomly allocated to the facilitator-guided individual DWM condition (n=202) or a repeated assessment control condition (n=101). The primary outcome was psychological distress (K10 score) at the posttreatment assessment. Secondary outcomes were posttraumatic stress disorder symptoms, functional impairment, social functioning, and personally identified problems. RESULTS: Intent-to-treat analysis indicated that participants in the DWM condition showed greater reductions in K10 scores than those in the repeated assessment control condition (posttreatment: β=-.563, SE=0.124; P<.001; Cohen d=0.56; 1-month follow-up: β=-.447, SE=0.140; P=.002; Cohen d=0.45). Similarly, those participants in the DWM condition reported greater improvements in posttraumatic stress disorder symptoms, well-being, social functioning, functional impairment, and personally identified psychological problems. No serious adverse events were reported. CONCLUSIONS: The findings provide the first evidence for the effectiveness of DWM in reducing psychological distress and improving overall functioning among urban refugees living in a transit setting. Individually supported self-help interventions such as DWM mayoffer an effective, feasible, and scalable approach to improving mental health for refugees.
21 May 2026
Read appraisal →JMIR formative research
Impact of Restriction-Resumption Protocols on Mood and Anxiety in Healthy Adults: Randomized Controlled Trial
BACKGROUND: Simple behavioral and cognitive actions can reduce symptoms of anxiety and depression. However, there is limited research investigating whether restricting those same actions increases symptoms and whether resuming those actions reduces symptoms. OBJECTIVE: The primary aim was to examine the impact of restricting, then resuming (the "restriction-resumption protocol"), 5 groups of actions called the Things You Do (TYD), on symptoms of depression and anxiety. Participant satisfaction with life and perceptions of changes in behavior and mental health were also evaluated. METHODS: In total, 70 adults were randomly allocated to an intervention group (IG) or a control group (CG). IG participants completed a 3-phase protocol over 8 weeks: a 2-week baseline period (phase A), 2 weeks of restricted TYD actions (phase B), and a 4-week resumption phase (phase C). CG participants were instructed to maintain their usual activities and routines. Primary outcomes included symptoms of depression (Patient Health Questionnaire-9), anxiety (Generalized Anxiety Disorder-7), and frequency of TYD actions. Secondary outcomes included satisfaction with life and perceived changes in mental well-being. Outcomes were measured weekly throughout the 8-week trial and again after the trial at week 9. RESULTS: Scores on outcome measures did not differ between groups during phase A and after the trial. However, by the end of phase B, IG participants showed significantly increased symptoms of depression and anxiety compared to CG participants (Ps<.001). Large within-group effect sizes were observed on the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 from baseline to the end of phase B (Cohen d>1.8) and from phase B to after the trial (Cohen d>1.9). Changes in satisfaction with life and evaluations of mental health corresponded with symptom changes. CONCLUSIONS: These findings demonstrate a relationship between the frequency of performing specific actions and symptoms of depression and anxiety. The restriction-resumption protocol has the potential to increase our understanding of causal mechanisms underlying common mental disorders and may lead to the development of new models of prevention and treatment. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12624001491550; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=388828&isReview=true.
21 May 2026
Read appraisal →PloS one
Optimizing bike-sharing station locations: A machine learning and artificial neural networks approach using geospatial and demographic data
In the modern world, public transportation amenities are noticeably on the rise, with urban bike-sharing systems becoming well-established in many major cities. However, not all cities have these systems, and planning optimal locations for bike-sharing stations is a complex task that requires consideration of many factors. To address this, the authors of this research paper developed a model to predict suitable locations for bike-sharing stations, utilizing machine learning techniques and artificial neural networks. These techniques utilized land cover and demographic data to train the model, achieving a high accuracy of 0.977. The predicted bike-sharing stations not only align with existing networks but also support their expansion, as many suggested locations are near major intersections and public transportation stops, confirming their suitability for the urban bike network. Additionally, the model was applied to Rzeszów, a city without a current bike-sharing system, where it successfully identified optimal locations for new stations. This demonstrates the methodology's practical applicability and its valuable support for planning bike-sharing infrastructure in urban areas.
21 May 2026
Read appraisal →Journal of medical Internet research
A Digital Toolkit for Weight Loss Maintenance in European Adults (NoHoW): 2×2 Factorial Randomized Controlled Trial
BACKGROUND: Digital approaches to weight management have the potential to produce cost-effective and scalable weight management solutions. Effective behavior change interventions typically promote self-regulation of energy balance behaviors, which may be enhanced by incorporating emotion regulation strategies. OBJECTIVE: This study aimed to evaluate the effectiveness of a digital behavior change toolkit for weight loss maintenance in European adults who had achieved ≥5% weight loss in the previous 12 months. We hypothesized that a combined intervention targeting self-regulation or motivation and emotion regulation would be more effective than either component alone, and that each would outperform an active control. METHODS: The Navigating to a Healthier Weight (NoHoW) trial was a 2×2 factorial randomized, single-blind, controlled trial involving 1627 adults who had achieved ≥5% weight loss in the previous 12 months (initial BMI ≥25 kg/m2) across 3 European centers (the United Kingdom, Denmark, and Portugal). The trial evaluated a digital toolkit for weight management subsequent to an initial ≥5% weight loss in the prior 12 months. Participants were assigned using adaptive stratified sampling to one of four groups: (1) self-regulation or motivation (n=403), (2) emotion regulation (n=416), (3) combined motivation and emotion (n=408), or (4) active control (generic content, regular self-weighing, and Fitbit use, n=400). The primary outcome was weight change from baseline to 12 months. Prespecified secondary outcomes included cardiometabolic markers. Linear models adjusted for recruitment center, sex, age group, BMI group, and pretrial weight loss. Subgroup analyses were conducted by sex. RESULTS: At 12 months, 76% (364/1627) of participants remained in the study. In the primary ITT analysis in all participants, none of the intervention arms (motivation, emotion, or combined) differed significantly from the active control for weight change at 12 months. Completer and per-protocol analyses produced similar patterns and did not change the overall interpretation. In the per-protocol sample, men regained 0.14 kg, and women regained 0.54 kg of their pretrial weight loss. Subgroup analyses indicated a small effect of the motivation intervention in men, but this was not clinically meaningful and did not alter the primary null findings. Nearly half of ITT participants regained weight, and no significant intervention effects were observed for cardiometabolic secondary outcomes. CONCLUSIONS: The NoHoW trial was the first large-scale, multicountry 2×2 factorial randomized controlled trial to evaluate a digital-only toolkit based on self-regulation or motivation and emotion regulation techniques for weight loss maintenance. NoHoW found no evidence in the primary ITT analysis that digital interventions targeting self-regulation or emotion regulation improved weight loss maintenance compared with the active control. A small subgroup effect in men should be interpreted cautiously and does not change this conclusion. The trial provides evidence on both the limitations and potential of digital behavior change interventions for long-term weight outcomes. Future digital interventions may benefit from enhanced engagement and tailored content to improve long-term weight outcomes.
21 May 2026
Read appraisal →JMIR formative research
Development, Feasibility, Acceptability, and Usability of an Artificial Intelligence-Powered Chatbot (Suzy) to Support Patients in Substance Use Disorder Recovery: Multiphase Study
BACKGROUND: Substance use disorder (SUD) remains a major public health crisis in the United States, with significant challenges in treatment access, retention, and workforce capacity. SUD care teams, including addiction medicine physicians and peer recovery coaches (PRCs), support patients receiving SUD treatment but face heavy workloads and burnout. Artificial intelligence (AI) innovations, particularly large language model (LLM)-based chatbots, may extend PRC support and provide patients with on-demand recovery support between clinic visits and PRC contacts. However, evidence on their development, feasibility, acceptability, and usability in addiction services remains limited. OBJECTIVE: This study describes the development, feasibility, acceptability, and usability of an AI-powered health coaching chatbot (Suzy) designed to support patients in SUD recovery. METHODS: A total of 2 clinicians, 5 researchers, and 2 technology developers led a small, multiphase pilot study. In the formative phase, they conducted focus groups and qualitative in-depth interviews with 12 health care professionals and 8 patients with substance use histories to specify chatbot functions and develop a rule-based chatbot. In phase 2, they conducted usability testing of the rule-based chatbot with 8 patients who reported substance use and completed standardized tasks, surveys, and qualitative interviews. Measures included the System Usability Scale (SUS), Net Promoter Score (NPS), and Single Ease of Use Question (SEQ). In phase 3, they developed an LLM-based chatbot co-designed and fine-tuned with PRCs and other SUD experts. RESULTS: Rule-based chatbot functions included craving management, appointment reminders, resource referrals, care team contacts, and goal setting. Usability task testing supported feasibility. In this small pilot sample, quantitative and qualitative feedback indicated acceptability and usability, with an average SUS score of 93 (benchmark 68), an NPS of 63 (benchmark 35), and a mean SEQ score of 6.5/7. Patients valued Suzy's approachable, nonjudgmental language and features that promoted accountability, self-monitoring, and 24/7 availability, while emphasizing that chatbots should supplement but not replace human support. The LLM-based chatbot development emphasized information accuracy, safety escalation protocols to mitigate risks of inappropriate chatbot responses, human-in-the-loop features, and expanded conversational flexibility and personal tailoring. CONCLUSIONS: In this pilot study, a rule-based chatbot designed to support SUD care demonstrated feasibility, usability, and acceptability. LLM-based chatbot development required more robust safety and emergency reporting features, while offering more patient-responsive conversational functions. By providing on-demand coaching, referrals, and reminders, Suzy may extend the reach of care teams, alleviate provider burden, and enhance patient engagement. Additional work is needed to understand how to best integrate Suzy into patients' recovery journeys to ensure human support remains accessible and prioritized. LLM evaluation was based on expert testing and safety review. Clinical effectiveness, including the impact on substance use, was not evaluated. Next steps include evaluating the LLM chatbot in real-world settings with larger samples and assessing its efficacy in reducing substance use.
21 May 2026
Read appraisal →Health policy and planning
Partial pictures: what routine health data can and cannot tell us about the quality of maternal and neonatal health services in Tanzania
Measurement of contact coverage of maternal and newborn health services may overestimate the benefits of the care that is provided, because the quality of care is not captured. It is therefore important to better understand the opportunities and challenges of capturing elements of care quality in routine health information systems (RHIS). This study explored healthcare workers' (HCWs), health sector managers' and policymakers' perspectives on the value and limits of routine health data to understand the quality of maternal and neonatal health services in Tanzania. We conducted qualitative research during two periods to capture perspectives across facility, district, regional and national levels. In Mtwara region in 2023, we conducted ethnographic observations at two hospital labour wards and 29 in-depth interviews with healthcare workers, hospital leaders, and district/regional managers. In 2025, we carried out 17 additional interviews with regional managers in Mtwara and with key national-level stakeholders. Our findings demonstrate that Tanzania's RHIS provides a valuable but partial picture of quality of care for maternal and neonatal health services. Care processes-including both provision and experience of care-are captured only to a limited extent. Using boundary object theory, we highlight how the same health information must serve diverse stakeholder needs. While there are opportunities to integrate more quality-of-care indicators, standardized RHIS cannot be expected to comprehensively capture the multifaceted nature of care quality. For quality measurement to support meaningful local health service improvement, a flexible, bottom-up approach is essential. However, the current emphasis on top-down oversight acts as a barrier for local-level data use. Relevant and feasible measurement of the quality of facility-based care requires a fundamental shift in current RHIS priorities-from systems that extract data for those 'up there' to platforms that also create value for those who provide care.
21 May 2026
Read appraisal →Oral health & preventive dentistry
Screening for Periodontitis Using Blood Biomarkers and Demographic Data: A Machine Learning Study
PURPOSE: Periodontitis is a common chronic disease associated with systemic conditions such as diabetes and cardiovascular disease. Diagnosis typically relies on dental examinations and radiographs, which may be underutilised by individuals who avoid, delay, or lack dental care. This study evaluated the potential of routine blood biomarkers and demographic data for screening moderate-to-severe periodontitis. METHODS AND MATERIALS: Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2011-2012 adults aged ≥ 30 years (N = 3,338). Periodontal status was classified using CDC/AAP definitions. An XGBoost classifier was trained on 77 features spanning demographics, complete blood count, glycemic and hemo-globin markers, heavy metals, and additional biochemical assays. Model performance was assessed with Accuracy, Precision, Recall, and F1 score. SHapley Additive exPlanations (SHAP) were used for interpretability. Subgroup analyses were conducted by age and gender. RESULTS: The model achieved 61.1% Accuracy, 57.4% Precision, 94.6% Recall, and an F1 score of 71.5%. Performance was higher in males (F1 = 78.2) than in females (F1 = 63.9%). SHAP identified age, gender, blood cadmium, blood lead, and glycohaemoglobin (HbA1c) as top predictors. CONCLUSION: Routine blood biomarkers and demographics can be leveraged for non-dental screening of periodontitis, offering a feasible preventive strategy in primary care. The model achieved high recall, minimising false negatives, and identified biologically plausible predictors. This approach may help flag at-risk individuals, particularly in underserved populations, and support integration of oral health into general medical care.
21 May 2026
Read appraisal →Health policy and planning
Pain, policy, and the opioid dilemma in sub-Saharan Africa: a systematic review of access, regulation, and health governance from 1990 to 2024
Sub-Saharan Africa (SSA) faces a dual opioid dilemma: widespread undertreatment of moderate to severe pain due to limited access to essential opioid analgesics, alongside increasing concern about misuse and diversion in selected contexts. Opioids are clinically indicated for severe cancer-related pain, advanced chronic illness, major trauma, surgery, and end-of-life care; yet, regional consumption remains disproportionately low relative to documented disease burden, indicating systemic under-provision rather than low need. This systematic review synthesizes evidence on opioid policy, regulation, access, and governance in SSA to examine how legal frameworks, institutional arrangements, political dynamics, and data systems shape medical availability. Following PRISMA and SWiM guidance, we reviewed peer-reviewed and gray literature addressing national drug control laws, regulatory implementation, procurement and supply systems, prescribing authority, and surveillance capacity; 33 studies met inclusion criteria. Across settings, restrictive or ambiguously interpreted legislation, multi-layered administrative controls, fragmented mandates across health and enforcement institutions, weak forecasting and distribution systems, concentrated prescribing authority, professional risk aversion, and chronic data gaps were consistently associated with constrained access. Concurrently, rising political and media attention to non-medical use, particularly of tramadol, has reinforced enforcement-oriented narratives that may further limit reform space. Persistent deficiencies in routine consumption data and unmet need assessment contribute to conservative import quotas and regulatory inertia. Addressing this imbalance requires proportionate, sequenced reform that strengthens data and forecasting systems, clarifies and aligns legal mandates with public health objectives, invests in workforce capacity and supply chains, and embeds safeguards against diversion while correcting avoidable under-treatment.
21 May 2026
Read appraisal →JMIR medical informatics
Machine Learning Prediction Model for Dyslipidemia and Its Association With Atherothrombotic Events in 3 Independent Cohorts From South Korea, Japan, and the United Kingdom: Algorithm Development and Validation Study
BACKGROUND: Dyslipidemia is a multifactorial and complex condition that warrants investigation through advanced analytical approaches such as machine learning (ML). Few previous ML studies predicting dyslipidemia have been validated across multiple international populations. OBJECTIVE: This study aimed to develop an ML model to predict the 5-year incidence of dyslipidemia using routinely collected health examination data. To ensure generalizability, the model was externally validated in populations from South Korea, Japan, and the United Kingdom. Furthermore, the clinical relevance of the model-derived risk was evaluated by examining its association with atherosclerotic outcomes, including acute myocardial infarction and cerebral infarction. METHODS: This study was conducted using 3 independent, large-scale, population-based cohorts. The discovery cohort from South Korea (n=471,650) was used for model training and internal validation, while 2 validation cohorts from Japan (validation A; n=7,255,685) and the United Kingdom (validation B; n=408,725) were used for external validation. We evaluated various ML-based models using 23 features extracted from regular health screening data to predict the new onset of dyslipidemia within 5 years. Shapley Additive Explanations values were calculated to assess feature importance. To ensure the robustness of the proposed ML model, we evaluated the risk of atherothrombotic events (acute myocardial infarction or cerebral infarction) based on the model probability (tertiles; T1, T2, and T3) using a Cox proportional hazards model. RESULTS: In the discovery cohort, soft-voting ensemble learning with Light Gradient Boosting Machine and categorical boosting exhibited performance metrics of area under the receiver operating characteristic curve (AUROC) of 0.783, precision of 37.9%, and area under the precision-recall curve of 0.469. The model showed moderate discriminatory performance in the external validation cohorts (cohort A: AUROC 0.744; precision 27.2%; and cohort B: AUROC 0.687; precision 5.07%). Shapley Additive Explanations value analysis identified smoking, alcohol intake, and physical activity as the most important features for predicting dyslipidemia. Finally, a higher model probability (T3 vs reference) was pronounced with an increased risk of acute myocardial infarction (adjusted hazard ratio 2.34, 95% CI 1.84-2.97) and cerebral infarction (adjusted hazard ratio 2.43, 95% CI 2.19-2.71). CONCLUSIONS: This multinational study developed and validated an ML-based model using routine health checkup data to predict the 5-year risk of new-onset dyslipidemia, which was also associated with atherosclerotic events.
21 May 2026
Read appraisal →BMJ open
Measurement of quality of stroke care with national electronic health records: a prospective cohort study during and after the COVID-19 pandemic
OBJECTIVES: To evaluate the value of linked electronic health records (EHRs) for measuring stroke care quality in England before and after the COVID-19 pandemic, focusing on metrics not routinely captured: stroke incidence, dispensing of secondary prevention medications and a proxy of disability-time spent at home after stroke ('home-time'). DESIGN: Prospective cohort study using national linked datasets. SETTING: England-wide health data linkage including the Sentinel Stroke National Audit Programme (SSNAP), primary and secondary care, dispensed medications and mortality records, accessed via National Health Service (NHS) England's Secure Data Environment. PARTICIPANTS: 425 675 adults with a first stroke between 1 January 2020 and 31 December 2023; data were available for 304 210 in primary care, 279 825 in hospital admissions, 220 470 in SSNAP and 59 465 in death records. MAIN OUTCOME MEASURES: Annual stroke incidence; first-year medication dispensing rates for antiplatelets, anticoagulants, antihypertensives and lipid-lowering agents (with a 1-month washout period) and home-time at 180 days post stroke. RESULTS: Stroke ascertainment was highest when combining all sources, with 10.8% of non-fatal ischaemic strokes recorded exclusively in primary care and 19.4% of fatal strokes identified solely through death records. Standardised annual stroke incidence rose from 227.6 (95% CI 226.1 to 229.0) to 244.8 (95% CI 243.4 to 246.3) per 100 000 over the study period including the COVID-19 pandemic. During the COVID-19 lockdown, non-fatal stroke recordings decreased while stroke-related deaths rose, indicating that recording quality was sensitive to shifts in healthcare-seeking behaviour during the pandemic. Among people with ischaemic stroke, 89.1% received an antiplatelet or anticoagulant, 44.5% an antihypertensive and 80.5% a lipid-lowering therapy. For haemorrhagic stroke, these proportions were: for anticoagulants 13.5%, antiplatelets 13.2%, antihypertensives 46.6% and lipid lowering 41.1%. Medication dispensing for stroke prevention declined with increasing age and comorbidity, but varied little by ethnicity, region or pandemic period. Mean home-time within 180 days of stroke was 166.6 (95% CI 166.4 to 166) days, decreasing with greater age (141.4 days for 90 years or older (95% CI 140.7 to 142.1)), deprivation (166.4 days (95% CI 166.1 to 166.6) for most deprived quintile) and stroke severity (137.4 days for National Institutes of Health Stroke Scale (NIHSS) score on arrival over 22 (95% CI 135.8 to 139.1)) and increasing with years from the COVID-19 pandemic 2023 (169.3 days (95% CI 169.0 to 169.5) vs 2020 164.4 days (95% CI 164.1 to 164.7)). CONCLUSIONS: Standardised stroke incidence increased significantly over the study period, highlighting a growing public health burden that persisted despite disruptions due to the pandemic although variation in case ascertainment and stroke coding practices was observed. While secondary prevention coverage for antiplatelets and lipids was high, lower rates of dispensing of antihypertensives, particularly in older and comorbid populations, potentially signal a target for improvement. Home-time represents a sensitive, person-centred outcome that exposes disparities linked to socioeconomic deprivation and clinical severity that can be used to enhance routine stroke audits. These findings justify the expansion of linked EHR infrastructure and the modernisation of governance frameworks to enable the longitudinal evaluation of care quality beyond the COVID-19 era.
20 May 2026
Read appraisal →Sexually transmitted infections
Complex role of digital health literacy in awareness and use of digital sexually transmitted and blood-borne infections testing: a structural equation modelling analysis of the 2022 GetCheckedOnline survey
BACKGROUND: Although digital health literacy (DHL) is recognised as a determinant of access to digital sexually transmitted and blood-borne infection (STBBI) testing, empirical evidence about its contribution to access disparities remains limited. We applied multidimensional DHL measures to examine inequities in awareness and use of GetCheckedOnline, British Columbia's (BC) publicly funded digital STBBI testing service. METHODS: We analysed data from GetCheckedOnline's 2022 community survey of English-speaking BC residents aged ≥16 years who were sexually active in the past year. Outcomes were awareness and use of GetCheckedOnline (yes/no). DHL was measured using latent factors from the eHealth Literacy Scale: Information Navigation, Resource Appraisal and Confidence in Use. Structural equation modelling (SEM) was used to estimate associations and mediation pathways between DHL, sociodemographic characteristics and service outcomes. Model fit was assessed using standard SEM indices. RESULTS: Among 1657 respondents (mean age 33 years, SD 11.77), Information Navigation was positively associated with awareness (β=0.162, p<0.001) and use (β=0.063, p=0.020) of GetCheckedOnline. Confidence in Use was positively associated with awareness (β=0.206, p=0.014) and use (β=0.115, p=0.020). In contrast, Resource Appraisal was negatively associated with awareness (β=-0.263, p=0.006) and use (β=-0.150, p=0.010). DHL factors mediated the effects of age, income, education and digital access on both outcomes. CONCLUSIONS: DHL operates as a multidimensional and socially patterned determinant of access to digital STBBI testing services. While information navigation and confidence in use facilitate access, higher resource appraisal may reduce use, potentially reflecting concerns about service fit, privacy or trust. Findings highlight the need for digital interventions that are not only accessible but also contextually relevant, trusted and responsive to the needs of diverse users.
20 May 2026
Read appraisal →Journal of the American Heart Association
Determinants of Successful Implementation: A Mixed-Methods Evaluation of a Team-Based Telehealth Hypertension Management Program for Underserved Patients
BACKGROUND: Hypertension management using home blood pressure monitoring-guided pharmacotherapy is more effective than clinic-based care, but the benefit is attenuated in underserved patients. We evaluated implementation determinants of a team-based telehealth hypertension management program providing home blood pressure monitoring-guided pharmacotherapy and self-management and social support. METHODS: We used Exploration, Preparation, Implementation and Sustainment, and Health Equity Implementation Frameworks for semistructured interviews and inductive/deductive coding using thematic analysis of qualitative data and quantitative analysis to evaluate team-based telehealth hypertension management program implementation facilitators, barriers, acceptability, appropriateness, and feasibility. We purposefully sampled 20 patients with hypertension and 16 clinic key players from 2 safety-net clinics in North Carolina. Quantitative measures were Acceptability of Intervention Measure, Intervention Appropriateness Measure, Feasibility of Intervention Measure, Patient Assessment of Chronic Illness Care, Organizational Readiness for Implementing Change (all measures' score ranged 1-5; higher score is better). We used concurrent embedded mixed methods (qualitative + quantitative) for convergence and complementarity. RESULTS: Five qualitative themes emerged around (1) staffing barriers, coordinated teamwork, and friendly study tools; (2) the program's patient and provider centeredness; (3) ease of home blood pressure monitoring; (4) personalized, comprehensive self-management calls; and (5) social support. Patients and clinic key players found the program acceptable (mean±SD, 4.42±0.84 and 4.56±0.59), appropriate (4.42±0.86 and 4.61±0.50), and feasible (4.40±0.89 and 4.44±0.53), respectively. Patient Assessment of Chronic Illness Care and Organizational Readiness for Implementing Change scores were 4.22±1.01 and 4.11±0.78, respectively. CONCLUSIONS: Implementing a team-based telehealth hypertension management program depends on its tailoring to patients and providers and having their endorsement; a user-friendly and trust-promoting model; and having a viable financial plan. Future studies should assess clinical and cost effectiveness of the program. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05424744.
20 May 2026
Read appraisal →PloS one
A computational text analysis of recent African digital health strategies and their attention to vulnerable populations
BACKGROUND: Digital health offers opportunities to transform healthcare systems and improve access to care, particularly in low- and middle-income countries. However, there is concern that national digital health strategies may inadequately address the needs of vulnerable populations, risking the reinforcement of existing health inequalities. OBJECTIVE: This study investigates the extent to which recent African national digital health strategies consider and prioritize vulnerable populations particularly at risk of digital exclusion (women, children and the elderly). METHODS: We conducted a computational text analysis of 13 recent national digital health strategy documents from African countries to identify major topical priorities within the strategies and to systematically assess the frequency and context of references to vulnerable populations. RESULTS: Most strategies focus on broad goals such as health system strengthening, infrastructure development, and stakeholder coordination. While there are mentions of women and children, these references are often indirect and not accompanied by concrete plans or dedicated actions. References to the elderly are especially rare. Few strategies include specific measures to ensure digital inclusion or equity for these vulnerable populations. CONCLUSIONS: Recent African digital health strategies currently prioritize systemic and infrastructural development, but the needs of vulnerable populations are often overlooked or superficially addressed. To prevent the digital divide from widening, national strategies should embed explicit equity targets, actionable plans, and mechanisms for meaningful inclusion and participation of all population groups.
20 May 2026
Read appraisal →The British journal of dermatology
Burden and risk of asthma and rhinitis in people with atopic dermatitis: global estimates from a hierarchical Bayesian model
BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease often associated with asthma and rhinitis. However, epidemiological evidence on these comorbidities remains fragmented and is largely limited to high-income countries. OBJECTIVES: To provide comprehensive global, regional and country-level estimates of the prevalence and odds ratios (ORs) of asthma, rhinitis and their subtypes among individuals with AD. METHODS: We systematically reviewed 278 studies retrieved from PubMed, Embase, Web of Science and CNKI (China National Knowledge Infrastructure). Standardized prevalence estimates and ORs were derived using a Bayesian hierarchical linear mixed-effects model. RESULTS: Among individuals with AD, the global prevalence estimate of asthma, rhinitis, allergic rhinitis, rhinoconjunctivitis, and coexisting asthma and rhinitis was 20.1% (ranging from 2.5% in Israel to 59.4% in India), 45.1% (ranging from 7.8% in Israel to 82.7% in India), 41.4% (ranging from 6.8% in Israel to 80.3% in India), 30.7% (ranging from 4.3% in Israel to 71.9% in India) and 10.4% (ranging from 1.1% in Israel to 40.8% in India), respectively. Estimates were higher when restricted to patients with AD diagnosed by dermatologists or physicians. The highest comorbid prevalence rates were found for India, Cuba, Finland and Puerto Rico. Compared with healthy control individuals, AD was associated with higher odds of asthma (OR 2.73; ranging from 1.59 in China to 6.64 in Ethiopia), rhinitis (OR 2.98; ranging from 1.73 in China to 7.23 in Ethiopia), allergic rhinitis (OR 2.42; ranging from 1.41 in China to 5.89 in Ethiopia), rhinoconjunctivitis (OR 4.21; ranging from 2.45 in China to 10.19 in Ethiopia), and coexisting asthma and rhinitis (OR 2.42; ranging from 1.41 in China to 5.89 in Ethiopia). CONCLUSIONS: This study provides the first globally standardized estimates of respiratory comorbidities in AD, and can inform clinical practice and public health policy. Atopic dermatitis is a common long-term inflammatory skin disease. It is also called eczema. It affects more than 200 million children and adults worldwide. People with the disease often have other conditions, particularly asthma and rhinitis. Asthma affects breathing and rhinitis causes sneezing or congestion. Most studies on these conditions have been in wealthy countries. They have also used a range of different research methods. This makes it difficult to compare and understand the global situation. In this study, researchers in China and the USA analysed data from 278 studies from around the world. We estimated how common asthma and rhinitis are in people with eczema in different regions and countries. We found that about 1 in 5 people with eczema have asthma and almost half have rhinitis. We also found that people with eczema are 2 to 4 times more likely to have these conditions than people without eczema. Some countries showed particularly high rates of these conditions. Our findings suggest that asthma and rhinitis are common problems for people with eczema. This is true no matter where they live. The information from this study may help doctors recognize and manage these conditions in people with eczema. These findings could also support future research to improve disease prevention and patient care.
20 May 2026
Read appraisal →Disaster medicine and public health preparedness
Hospital Medical Surge Capacity Assessment and Planning Tools for Disaster Response: A Systematic Review and Meta-analysis
BACKGROUND: Hospital surge capacity is pivotal for disaster response, yet the effectiveness of assessment and planning tools remains underexplored. OBJECTIVE: This systematic review evaluates the reliability, validity, and applicability of surge capacity tools across disaster scenarios. METHODS: Following PRISMA guidelines, we analyzed 24 Q1 studies (PubMed, Scopus) using the PICO framework. Risk of bias was assessed via ROBINS-E, and meta-analysis (random-effects model) quantified pooled effect sizes (ES). Subgroup analyses compared simulation tools, surveys, and resource strategies. RESULTS: The combined ES was 0.74 (95% CI: 0.67-0.82), indicating moderate improvement in preparedness. Simulation tools (Group A) showed the highest consistency (ES = 0.81, I2 = 0%), while resource strategies (Group C) had wider variability (ES = 0.71, I2 = 74.42%). Egger's regression revealed publication bias (P = 0.004), and heterogeneity was substantial (I2 = 76.70%). CONCLUSIONS: Simulation-based tools are most effective for surge capacity, whereas resource strategies require contextual adaptation. Policymakers should prioritize standardized benchmarks and DSS integration, with future research addressing equity and real-world implementation gaps.
20 May 2026
Read appraisal →International journal of biometeorology
Machine learning and dose response effect models: an integrated approach to analyze the association between environmental variables and Cuneo Emergency Department admissions for Acute Otitis Media (2007-2015)
Acute otitis media (AOM) is a leading cause of pediatric Emergency Department visits, particularly among children under five years of age. Although its seasonal pattern is well established, the role of air pollution and meteorological factors remains unclear. This study aims to investigate their impact on daily AOM visits by integrating machine learning and epidemiological approaches. We conducted a retrospective analysis of pediatric AOM diagnoses (2007-2015) at S. Croce and Carle Hospital (Cuneo, Italy). Predictors included PM10, NO₂, O₃, and eleven meteorological variables. Ensemble machine learning models (Random Forest, XGBoost, and AdaBoost) were trained and validated using 10-fold cross-validation. Model interpretability was assessed through SHAP values. Distributed Lag Nonlinear Models (DLNM) were applied to estimate delayed exposure-response relationships over lag periods of 0-1, 0-3, 0-5, and 0-10 days, with results expressed as Relative Risks (RRs) and 95% Confidence Intervals (CIs). AdaBoost showed the best performance (R² = 0.974; MAE = 0.019 cases/day; cross-validated R² = 0.987). SHAP analysis identified mean temperature as the most influential predictor (44%), while PM10, NO₂, and O₃ each contributed approximately 10%. DLNM analysis confirmed a strong and consistent effect of temperature across all lag periods (RR > 1.20, CI > 1). Moderate associations were observed for NO₂ and PM10 (RR: 1.02-1.04). O₃ exhibited smaller but significant effects at shorter lags (RR = 1.01 at 0-1 days; RR = 1.02 at 0-3 days; CI > 1). Environmental factors, particularly temperature, play a significant role in pediatric AOM incidence. The integration of machine learning and DLNM enhances predictive accuracy and improves the understanding of exposure timing. These findings support the development of early warning systems and targeted preventive strategies under adverse environmental conditions. Further validation in larger urban settings is needed.
20 May 2026
Read appraisal →Cancer causes & control : CCC
Prediction models for early detection and diagnosis of lung cancer in people who have never smoked: a systematic review and critical appraisal
BACKGROUND: Never-smokers can develop lung cancer, but this possibility is often overlooked by patients and physicians. We conducted a systematic review to identify existing prediction models that could be implemented in primary care or at a population level to facilitate early detection and diagnosis of lung cancer in never-smokers. METHODS: This study was registered on PROSPERO (ref: CRD42023374471). We systematically searched literature on the Medline, Embase, PsycINFO, and CINAHL databases published before 22 January 2025, with additional hand searching. Primary care or population-level data from subjects including never-smokers had to be used for model derivation. Studies involving specialized tests (radiological or genetic) were excluded. We used CHARMS to guide data extraction and critical appraisal, the TRIPOD statement for model evaluation, and PROBAST for risk of bias assessment. RESULTS: Among 2,431 studies retrieved, 31 models were included. Eight models were developed exclusively for never-smokers, but none were at low risk of bias. Among 23 models derived from never- and ever-smokers, five were at low risk of bias. Two were diagnostic models with 1-2 years prediction horizons, and three were prognostic models with 2-10 years prediction horizons. Methodological issues from the included studies were identified, analyzed, and discussed. CONCLUSION: This systematic review critically appraises and summarizes key information from currently available prediction models for lung cancer in never-smokers. The findings can inform future research to improve care and services for this underserved population.
20 May 2026
Read appraisal →BMC public health
Interventions against loneliness and social isolation in older adults- a systematic review.
BACKGROUND: Loneliness is a growing health and social challenge. The COVID-19 pandemic boosted feelings of loneliness for many people. To combat loneliness, a wide range of interventions have been developed and evaluated for their efficacy and effectiveness. As a result, many new interventions to alleviate loneliness have been developed, especially technological interventions. Therefore, the objective of this study was to conduct a comprehensive and up-to-date systematic review to identify interventions aimed at loneliness and social isolation among adults, 60 years and older published during or post-pandemic. METHODS: A comprehensive literature search was conducted for studies between 2020 and 2024 across five online databases: MEDLINE via PubMed, Web of Science, Scopus, Cochrane Library, and CINAHL. Title and abstract screening, critical appraisal of the studies, and data extraction were performed by two independent reviewers. A narrative approach was adopted to assess and integrate the diverse findings from the research. RESULTS: Ultimately, 79 studies were included in this systematic review. The results are structured based on the categorization of the interventions, which includes differentiation between analogue interventions, technological interventions and multicomponent (analogue and technological) interventions. The effectiveness of analogue interventions, particularly community-based interventions such as group meetings, social participation programs, and educational or psychological interventions, tended to be superior to that of technological interventions. CONCLUSIONS: The combination of analogue and technological interventions in particular produced promising results regarding a decrease of loneliness. Specific interventions must be tailored to the target group and setting and regularly reevaluated. The aim now should be to implement these interventions comprehensively and monitor their effectiveness over several years. Future research should focus on differentiating the circumstances under which various forms of intervention are effective. TRIAL REGISTRATION: PROSPERO systematic review registration: CRD42024538755.
20 May 2026
Read appraisal →The Journal of clinical endocrinology and metabolism
Predicting incident type 2 diabetes using wearable activity and polygenic risk: A survival-modeling study in All of Us
BACKGROUND: Evidence is limited on whether daily step counts are uniform across individuals or whether combining them with genetic risk improves prediction of type 2 diabetes (T2D), both essential for precision prevention. We aimed to assess whether objectively measured daily step count and Polygenic Risk Score (PRS) predict the incidence of T2D, and to evaluate the predictive performance of machine-learning models. METHODS: We conducted a prospective cohort study of 4589 adults in the National Institutes of Health's All of Us Research Program with valid Fitbit step data and whole-genome-derived PRS, excluding individuals with T2D before or within a 180-day lead-in period. Incident T2D was defined by HbA1c ≥ 6.5%, plasma glucose ≥126 mg/dL, or an All of Us T2D condition record. We evaluated Cox and machine-learning survival models. FINDINGS: Over a median of 2.92 years (15 340 person-years), 265 participants developed T2D (5.77% cumulative incidence; 17.27 per 1000 person-years). Risk-reducing thresholds were ∼7000 steps/day (P < .001) but differed by PRS group (∼7800 high vs ∼5800 low; P < .001). Each additional 1000 steps/day was associated with lower T2D risk (adjusted hazards ratio, 0.83; 95% CI, 0.79-0.88; P < .005), whereas each 1-SD higher PRS was associated with higher T2D risk (adjusted hazards ratio, 2.62; 2.32-2.96; P < .005). Adding steps to a clinical model increased the C-index from 0.748 to 0.774; adding PRS increased it to 0.867. Penalized Cox achieved the highest discrimination (C-index 0.859), followed by survival support vector machine (0.85) and classical Cox (0.846). Calibration was best with Random Survival Forests. INTERPRETATION: Step-count thresholds for reducing T2D risk varied across genetic risk groups, indicating that step counts do not confer uniform protection. Step counts and PRS provided independent, complementary predictive information, and their combination improved prediction of incident T2D.
20 May 2026
Read appraisal →BMJ open
Implementation of a clinical decision support tool for postpartum depression: protocol for a prospective randomised clinical trial
INTRODUCTION: Perinatal mood and anxiety disorders affect more than one in five pregnant individuals. Despite the large percentage of individuals impacted by mood disorders, they continue to remain underdiagnosed and undertreated. Recent interventions such as risk prediction modelling offer opportunities to predict patients at risk prior to symptom onset. Leveraging technology platforms such as electronic health records allow for timely diagnosis and intervention. To date, there are no established clinical decision support (CDS) tools. We hypothesise that subjects who use a CDS aid will find them acceptable, appropriate and feasible. METHODS AND ANALYSIS: We will conduct a pilot randomised clinical trial at three Weill Cornell Medicine clinics with randomisation at the clinician level. Patients in the control arm will receive usual care, while those in the intervention arm will receive CDS. The primary implementation outcomes are the acceptability, appropriateness and feasibility. The effectiveness outcomes are mental health service utilisation, EuroQol 5 Dimensions questionnaire (EQ-5D), Edinburgh Postnatal Depression Scale and social support measured by the perceived support scale. We hypothesise that stakeholders will find the CDS acceptable, and the intervention arm will have lower mental health service needs compared with control. ETHICS AND DISSEMINATION: This study has been approved by the Weill Cornell Medicine Internal Review Board. IRB Protocol# 23-07026254. TRIAL REGISTRATION NUMBER: NCT06818734.
20 May 2026
Read appraisal →PloS one
The carbon footprint of surgical operations: 2023-2025 systematic review update
Surgical care significantly contributes to greenhouse gas emissions, with operating rooms consuming three to six times more energy than other departments relying heavily on single-use materials and anaesthetic gases. We conducted a systematic review of literature from 2023 to 2025 following PRISMA guidelines. The PubMed, Scopus and Healthcare LCA databases were searched, and eligibility criteria were applied. A total of 26 studies met inclusion criteria. Data were extracted on each study's scope and system boundaries, reported emission values, identified carbon hotspots, and any mitigation strategies evaluated. A structured quality assessment was conducted to evaluate the reliability of the included studies and to identify potential sources of bias. The included studies demonstrated wide variability in reported carbon footprints of surgery, ranging from under 5 kgCO₂e for minor procedures to over over 400 kgCO₂e for complex single-stage operations and approximately 1,000 kgCO₂e for whole multistage patient pathways. This systematic review underscores that surgical operations could have a significant carbon footprint, with emissions hotspots concentrated in consumable materials and energy consumption. It also reveals substantial variability and methodological heterogeneity in how surgical carbon footprints are calculated, pointing to the urgent need for standardized life-cycle based frameworks in surgical settings. Establishing common standards will enable more reliable benchmarking of surgical emissions and better comparisons across studies.
19 May 2026
Read appraisal →JMIR infodemiology
Performance of Large Language Models in the Cognitive Analysis of Misinformation: Evaluation Study
BACKGROUND: Public discourse is significantly impacted by the rapid spread of misinformation on social media platforms. Human moderators, while capable of performing well, face many challenges due to scalability. While large language models (LLMs) show great potential across various language tasks, their capacity for cognitive and contextual analysis, in detecting and interpreting misinformation, remains less evaluated. OBJECTIVE: This study evaluates the effectiveness of LLMs in detecting and interpreting misinformation compared to human annotators, focusing on tasks requiring cognitive analysis and complex judgment. Additionally, we analyze the influence of different prompt engineering strategies on model performance and discuss ethical considerations for using LLMs in content moderation systems. METHODS: We evaluated 4 OpenAI models against a panel of human annotators using a subset of posts from the MuMiN dataset. Each model and human annotator responded to structured questions on misinformation, following an established cognitive framework. Both human annotators and LLMs also provided scores indicating how confident they were in their responses. Various prompting strategies were used in this research, including: 0-shot, few-shot, and chain-of-thought, with performance evaluated through precision, recall, F1-score, and accuracy. We used statistical tests, including the McNemar test, to quantitatively assess differences between LLM and human ratings of misinformation. RESULTS: GPT-4 Turbo with chain-of-thought prompting achieved the highest performance of all LLMs for detecting misinformation, with an accuracy of 67.2% and an F1-score of 78.3%, but was outperformed by human annotators, who achieved 70.1% accuracy and an F1-score of 81%. LLMs performed well in tasks involving logical reasoning and straightforward misinformation detection, but struggled with complex judgments, including detecting sarcasm, understanding misinformation, and analyzing user intent. LLM confidence scores positively correlated with accuracy in simpler tasks (r=0.72, P<.01) but were less reliable in subjective and complex contextual evaluations. CONCLUSIONS: LLMs show significant potential for automating misinformation detection. Their limitations in understanding and interpreting these posts highlight the current necessity of human oversight. A hybrid framework combining LLMs for preliminary screening with human moderators for more complex evaluation presents a promising future direction. Future research could prioritize the fine-tuning of LLMs using datasets that emphasize cognitive and emotional linguistic features, alongside the development of advanced prompting techniques.
19 May 2026
Read appraisal →Environmental monitoring and assessment
Air pollution-related health impacts from domestic waste burning and associated interventions: the merits of a traditional versus machine learning scoping review methodology
Regularly updating repositories of air pollution impacts on health is essential for evidence-based policies, interventions, and progress monitoring. However, this is often time-consuming and labour-intensive. Automation can ensure up-to-date evidence; reduce retrieval, screening time, and costs; and make information accessible to non-academic stakeholders. This study investigated whether a machine learning approach can perform any stages of a traditional scoping review on the health impacts, policies, and interventions related to air pollution due to domestic waste burning. A traditional approach was conducted in parallel with machine learning methods enabling a comparison of the efficiency and quality of the partially automated approach against the manual review. Findings from the two approaches were compared and the final set of included articles were considered for (1) reported impacts of waste burning on health outcomes and (2) recommendations on solutions and interventions to prevent/reduce adverse effects on health from waste burning. We found a range of health impacts associated with waste burning, including low birth weight, hypertensive disorders of pregnancy, adverse respiratory outcomes like asthma and wheeze, cancer risk, and mortality. Few studies proposed solutions or evaluated the effectiveness of interventions. The ML approach showed a tendency towards false positives, which are preferable to false negatives (where relevant papers were excluded). Results showed that the model can conduct initial searches and decisions for the review. However, the articles included in the model should be screened manually for final acceptance. Therefore, we propose a hybrid approach be used until the automated model can be further refined.
19 May 2026
Read appraisal →Gut and liver
Global Prevalence of Functional Abdominal Pain Disorder among Children and Adolescents According to the Rome III and IV Criteria: A Systematic Review and Meta-Analysis
BACKGROUND/AIMS: Despite the global burden of functional abdominal pain disorder (FAPD) and its four subtypes (irritable bowel syndrome [IBS], functional dyspepsia [FD], abdominal migraine [AM], and functional abdominal pain not otherwise specified [FAP-NOS]), studies involving an estimation of FAPD prevalence based on the Rome III or IV criteria are limited. Therefore, we aimed to estimate the prevalence of FAPD and its four subtypes. METHODS: A comprehensive literature search was conducted in PubMed/MEDLINE, Embase, Google Scholar, and the Cochrane Library. Studies that were performed with the general population and applied Rome III or IV diagnostic criteria were included. Data were extracted to estimate the prevalence of FAPD using a random-effects model with 95% confidence intervals (CIs). Heterogeneity was assessed using the I2 statistic. The study protocol was preregistered with PROSPERO (CRD420251004116). RESULTS: The overall prevalence of FAPD was 10.89% (95% CI, 9.51% to 12.48%), with pooled prevalence rates of 11.84% (10.29% to 13.61%) with the Rome III criteria and 8.42% (6.10% to 11.62%) with the Rome IV criteria. With the Rome III criteria, IBS had the highest prevalence, while FD had the lowest. In contrast, with the Rome IV criteria, the prevalence of IBS, AM, and FAP-NOS decreased, whereas FD became the most prevalent, affecting approximately one in 23 individuals, compared to one in 51 individuals affected by IBS, one in 68 individuals affected by AM, and one in 115 individuals affected by FAP-NOS. Additionally, females exhibited higher prevalence rates of FAPD and all its subtypes than males. CONCLUSIONS: The diagnostic criteria of Rome IV are stricter than those of Rome III, which likely affects the estimated prevalence of FAPD and its subtypes.
18 May 2026
Read appraisal →Environmental research
Association between air pollution and chronic cough: Evidence from a systematic review and meta-analysis of observational studies
BACKGROUND: Chronic cough is a common and debilitating respiratory symptom, yet its association with air pollution remains insufficiently understood. METHODS: We conducted a systematic review and meta-analysis of observational studies evaluating the association between air pollution and chronic cough. Searches of Medline, Embase, Scopus, and GeoBase were completed up to February 14, 2025. Studies were eligible if they reported quantitative associations between air pollution and exposures and chronic cough outcomes. Two reviewers independently screened studies, assessed quality, and extracted data. Random-effects models were used to estimate pooled odds ratios (ORs) with 95% confidence intervals. RESULTS: Of 1250 articles screened, 53 studies were reviewed, and eight were included in meta-analysis. Pooled ORs per 10 μg/m3 increase in exposure were 1.10 (95% CI: 0.99-1.22) for PM2.5 and 1.04 (95% CI: 1.02-1.06) for NO2. Heterogeneity was low to moderate (I2: 18.9% for PM2.5; I2: 0.0% for NO2), and there was no evidence of publication bias (Egger's test p = 0.98 and 0.47, respectively). Stratified analyses revealed stronger associations in adults and males. Evidence on progression from chronic cough to more severe respiratory conditions was limited, highlighting a critical gap for evidence-informed clinical follow-up and public guidance to prevent progression. CONCLUSION: Our findings highlight that chronic cough is an overlooked consequence of air pollution exposure and emphasize the need for health care professionals to consider environmental factors when managing persistent cough. Strengthening air quality control and early detection strategies could help reduce the respiratory disease burden.
18 May 2026
Read appraisal →European journal of pediatrics
Prevalence of common respiratory viruses of infants with respiratory tract infections in European countries in the past decade: a systematic review and meta-analysis comparing between the pre-COVID-19, pandemic, and post-COVID-19 periods
UNLABELLED: The purpose of this study is. to determine the leading cause of respiratory tract infections over the decade; this review examined the proportions of airway viruses in infants with respiratory tract infections in Europe before, during, and after the COVID-19 pandemic. The protocol for this systematic review was registered in the PROSPERO database (CRD42024497097). Literature searches in PubMed, Embase, Scopus, and Web of Science (WoS) identified 20,453 studies reporting respiratory viral testing in Europe over the past decade (2012/13-2022/23). Eligible studies were English-language full-text or grey articles with low risk of bias and complete data, and reports that explicitly provided the number of positive airway virus cases (n, virus) and the total infant population (N). Risk of bias was assessed using the Hoy et al. scoring system. Pooled prevalence estimates (pooled proportion [95% CI]) were calculated for pre-, during-, and post-COVID-19 periods using proportional meta-analysis with the MetaProp package in R. Fifty studies before, ten studies during, and 18 studies after the COVID-19 pandemic were eligible for proportional meta-analyses of viral testing in infants. Before the pandemic, the predominant viruses in infants with respiratory infections were Respiratory Syncytial Virus (RSV) (0.48 [0.41-0.56]), Human rhinovirus (HRV) (0.24 [0.18-0.29]), and Influenza virus (IV) (0.08 [0.04-0.12]). Post-pandemic, the leading viruses were RSV (0.63 [0.51-0.75]), HRV (0.25 [0.11-0.40]), and IV (0.10 [0.00-0.20]) again. CONCLUSIONS: RSV and HRV remained the two most identified viruses in infants with respiratory infections, pre- and post-COVID-19 pandemic. Interestingly, both RSV and IV were suppressed during the pandemic. The trajectory dynamics of respiratory viruses were divergent, with resilient viruses (RSV, HRV, and IV) regaining dominance more rapidly than persistently suppressed viruses. WHAT IS KNOWN: • The COVID-19 pandemic induced an infection precautions policy, which reduced the spread of respiratory infectious diseases. • Respiratory Syncytial Virus (RSV) was estimated as one of the most common causes of respiratory infections in infants. Still, there are no reports summarising the geographical distributions of the various viral agents of infant respiratory diseases. WHAT IS NEW: • This meta-analysis shows that the prevalence of RSV and HRV infections in infants remains high in Europe following the COVID-19 pandemic and the associated precautionary policy. Furthermore, RSV proportionally experienced a marked reduction during COVID-19 pandemic (lockdown periods). However, the immunological debt may have led to a re-emergence in RSV positivity after the lockdown periods. • Our proportional meta-analysis indicates the heterogeneous post-pandemic recovery patterns of each respiratory virus commonly identified in infants, where HRV was shown to be resilient whilst RSV was rapidly rebound.
18 May 2026
Read appraisal →Computer methods and programs in biomedicine
Prompt-to-policy: Leveraging large language models to guide deep reinforcement learning in public health emergencies
Rapid and effective decision-making is critical in public health emergencies, where resource allocation must balance multiple objectives under uncertain conditions. Traditional optimization methods often struggle with computational complexity and real-time, heterogeneous data. To address these challenges, we propose a hybrid intelligent agent combining an enhanced Double Deep Q-Network (D2QN-JDA) with large language models (LLMs). The D2QN-JDA improves learning stability and adaptability through joint state-action inputs, dynamic exploration rate, and adaptive reward normalization. The LLM component uses Retrieval-Augmented Generation (RAG) to integrate structured and unstructured data for real-time decision support. Experiments based on data from the Hong Kong COVID-19 outbreak show that the D2QN-JDA outperforms dynamic programming, greedy algorithms, genetic algorithms, and Q-learning, achieving reductions in cost. The LLM component also outperforms manual and regex methods in both single- and multi-point data extraction, enhancing accuracy, recall, F1 score, cost, and time. Our framework effectively addresses complex, multi-objective resource allocation in public health crises.
17 May 2026
Read appraisal →Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
Injuries from falling out of bed in infants under 1 year of age: a systematic review
CONTEXT: Falls from beds are a leading cause of unintentional injuries in infants under 1 year of age. While most cases result in mild outcomes, the potential for severe injuries, such as skull fractures or intracranial haemorrhages, exists. Despite the prevalence of these incidents, no systematic review has focused specifically on injuries from bed falls in this specific age. OBJECTIVE: To evaluate the risk and severity of injuries caused by falls from beds in infants under 1 year of age through a systematic review. DATA SOURCES: We searched in PubMed, Embase, Cochrane Library and Lilacs Scielo for studies published between 1984 and December 2024. STUDY SELECTION: We included observational studies that reported injuries from falls from beds in infants under 1 year. DATA EXTRACTION: We extracted the relevant data from the included study details, recruitment setting, study design, sample size and outcome measures. We conducted a quality assessment using the Newcastle-Ottawa Scale. RESULTS: Out of 297 initially identified studies, three met inclusion criteria, comprising a total of 2034 infants under 1 year of age. Most falls resulted in minor or no injuries. Warrington et al reported <1% of cases leading to concussion or fractures. Samuel et al identified two cases of intracranial haemorrhage and linear skull fractures without intervention. Kolulu et al observed significant injuries, including skull fractures and cerebral contusions, in 10.2% of infants. CONCLUSIONS: Falls from beds are frequent in infants under 1 year, with most resulting in minor outcomes. However, serious injuries occur in around 5% of infants below 1-year old, emphasising the need for prevention strategies and clinical guidelines for managing post-fall assessments. Further research is required to refine understanding and improve prevention and management practices. PROSPERO REGISTRATION NUMBER: CRD42024626255.
17 May 2026
Read appraisal →JMIR mental health
Factors Influencing the Initiation and Continued Engagement of Digital Mental Health Tools Among Adults: Theory of Planned Behavior-Informed Systematic Review
BACKGROUND: Digital mental health tools (DMHTs) offer scalable support, but engagement varies. Understanding the shapes of initiation and ongoing use is essential for effective design and implementation. OBJECTIVE: This study aims to synthesize determinants of adults' initiation and engagement with DMHTs, organized through two lenses: (1) psychological factors aligned with the theory of planned behavior (TPB) and (2) design and access features. METHODS: A systematic search of 9 databases (June 2025) identified qualitative and mixed methods primary studies reporting end-users' experiences with DMHTs. Studies were screened and reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Quality appraisal used quality assessment with diverse studies (QuADS). Data were synthesized using a framework-guided thematic approach, mapping findings to TPB constructs and complementary design and access domains. RESULTS: A total of 22 studies met inclusion criteria. Findings clustered into 2 interdependent domains. TPB constructs explained how beliefs, social expectations, and perceived control shaped decisions to start and persist with DMHTs. Design and access features frequently acted through these same pathways, especially by altering perceived behavioral control (PBC), with cost, connectivity, device constraints, and time flexibility affecting feasibility, with content design and privacy shaping perceived value and trust. Perceived fit (goals, cultural or linguistic relevance, and routine alignment) consistently influenced both initiation and continuation. Several features operated bidirectionally; depending on context, the same feature could facilitate or hinder engagement. CONCLUSIONS: Engagement with DMHTs is jointly determined by users' beliefs and the design and access conditions within which tools are offered. Implementation should pursue a dual strategy, strengthening willingness to seek support (addressing attitudes, norms, and perceived control) while engineering low-effort, trustworthy, and context-appropriate experiences. Priorities include equity-focused policies (data costs, devices, and connectivity), transparent data practices, co-design with diverse communities, and consistent, theory-informed outcome measures.
17 May 2026
Read appraisal →Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
Large language models in public health: opportunity or threat? The case of button battery injuries.
BACKGROUND: Button battery (BB) injuries in children represent a severe and growing public health burden. The literature on the topic is extensive; however, there is a notable lack of structured public health initiatives addressing the problem. The present study aimed to test the feasibility of using large language models (LLMs) to draft recommendations for preventing and managing BB ingestion in children. METHODS: A set of questions was generated and submitted to ChatGPT-4o and ChatGPT-o1-preview. Questions were based on statements and websites of scientific societies and not-for-profit organisations and were developed to produce comprehensive recommendations that provided information on BB risks, primary and secondary prevention, clinical management and follow-up, and general public health initiatives. Two independent reviewers rated the accuracy and readability of the questions submitted to the LLMs. The accuracy was rated using a four-level scale, while the readability was assessed using two established readability tools, the Flesch Reading Ease (FRE) and the Flesch-Kincaid Grade Level (FKGL). RESULTS: None of the answers provided by the LLMs were rated as completely incorrect or partially incorrect. ChatGPT-o1-preview outperformed ChatGPT-4o in accuracy, with eight answers rated as accurate and complete. Both models showed similar readability levels, with high FKGL and FRE scores indicating college-level comprehension. DISCUSSION: LLM demonstrated a strong performance in this study, with no responses rated as incorrect or partially incorrect, showing its great potential and feasibility for use in public health. CONCLUSIONS: The present findings suggested the potential feasibility of LLMs in public health for preventing paediatric injuries.
17 May 2026
Read appraisal →European journal of pediatrics
Leveraging artificial intelligence to predict non-adherence to pediatric immunization schedules: a systematic review
UNLABELLED: Immunization is one of the most effective interventions to prevent infectious diseases. Identifying individuals at risk of non-adherence to immunization schedules could enable early interventions to improve coverage. With the increasing availability of large datasets with sociodemographic, medical, and geographic data, artificial intelligence (AI) offers new possibilities for identifying predictive patterns. We performed a systematic literature review of original studies that used AI to predict immunization non-adherence in children. Searches were conducted in PubMed, Embase, and Web of Science and no restrictions were applied regarding publication year, language, or study design. Study characteristics, dataset size, AI methods, performance metrics, and validation approaches were extracted. Risk of bias was assessed using PROBAST + AI. A total of 843 records were identified; after screening, 12 studies were included. Nine of 12 studies were conducted in low- and middle-income countries, used cross-sectional survey data, and analyzed vaccines from routine immunization schedules. Model performance was generally high; 9/12 studies reported an accuracy or an area under the receiver operating characteristic curve exceeding 80%, but no study conducted external validation. Predictors clustered into seven categories: maternal, paternal, family, child, geographic, wealth, and others. Among maternal and child-related factors, prenatal care and previous immunization history had a high predictive weight. CONCLUSION: AI demonstrates a promising potential for identifying individuals at risk of vaccine non-adherence. However, the lack of external validation raises concerns about model overfitting and limits real-world applicability. Demographic health surveys were routinely repeated across countries and time periods and could therefore represent an ideal resource for external validation. WHAT IS KNOWN: • Geographic, sociodemographic, and medical factors contribute to non-adherence to the immunization schedule. • Identifying these individuals can guide early interventions to improve immunization coverage. WHAT IS NEW: • Artificial intelligence can reveal unknown influential factors; prenatal care and delivery setting emerged as key factors in this systematic review.
17 May 2026
Read appraisal →JMIR mHealth and uHealth
Smartphone Apps for Cannabis Cessation: Quality Assessment and Content Analysis
BACKGROUND: Over the past 2 decades, global rates of cannabis use have risen significantly, especially among young adults. This has corresponded to an increase in cannabis-related problems and hospitalizations. Thus, there has been significant interest in developing new interventions that can help facilitate cannabis cessation and reduce hospitalization rates. Specifically, mobile apps have emerged as scalable and accessible stand-alone or adjunct interventions that can help individuals with cannabis use disorders. OBJECTIVE: This study aimed to evaluate the quality of free cannabis cessation apps available on both the Apple App Store and Google Play Store, focusing on the analysis of their features, content, and adherence to evidence-based practices. METHODS: A systematic search was conducted in April 2023 using a variety of keywords. The apps were deemed eligible if they were free, available in English, accessible on both the Apple App Store and the Google Play Store, and related to cannabis cessation. Eligible apps were used for at least 1 month and were rated on the Mobile App Rating Scale by 2 reviewers. Interrater reliability was excellent, with a weighted Cohen κ of 0.893 (95% CI 0.835-0.943). RESULTS: Four apps were included in the analysis, namely, "Grounded-Quit Weed," "Quit Weed," "Marijuana Addiction Calendar," and "Marijuana Anonymous." The mean overall quality score of the apps was 3.4 out of 5, indicating poor to acceptable quality. The apps scored the highest on the "functionality" section and the lowest on the "information" section. Of the 4 apps, 3 focused on tracking cannabis use and duration of abstinence, whereas 1 focused on peer support. A limited number of cannabis cessation apps were identified, and those that were available were of low quality due to a lack of evidence-based information. CONCLUSIONS: This study is the first to evaluate the current availability and quality of mobile apps designed for cannabis cessation. Unlike previous research that broadly assessed cannabis-related mobile apps, this study focuses on the limited number of free cannabis cessation tools, reflecting what is most available to the general population. The findings highlight a significant gap between the growing demand for virtual cessation tools and the quality of existing options. With the rising global prevalence of cannabis use disorders, there is an increasing need for robust, accessible, and evidence-based therapeutic options. While mobile health apps may be a viable option to support cannabis cessation, the current landscape is limited by poor quality apps and a lack of evidence-based information. From a real-world perspective, this study highlights the need for users to exercise caution when relying on current cannabis cessation apps and underscores the urgent need for the development and evaluation of new evidence-based digital interventions.
17 May 2026
Read appraisal →European journal of preventive cardiology
Elevated blood pressure levels among 533 167 adults living in Sub-Saharan Africa: a systematic review and meta-analysis
AIMS: Synthesizing contemporary data from sub-Saharan African countries, we did a systematic review and meta-analysis of blood pressure (BP) levels and hypertension among adults living in the region. METHODS AND RESULTS: We searched PubMed and other databases to identify studies published from 1 January 2010 to 31 December 2021. We used a random-effects model to estimate the pooled-prevalence of hypertension and mean systolic/diastolic BP overall and on a sex- and age-specific basis. Heterogeneity (I²) was assessed via the χ² test on Cochran's Q statistic. We identified 170 high-quality studies (195 samples) comprising 533 167 adults living in 26 countries. The pooled prevalence of hypertension was 30.5% (95% CI 28.4-32.6%). Overall mean systolic/diastolic BP was 128 (95% CI 127-129)/80 (95% CI 79-80) mmHg, with males recording higher mean BP levels (3.10 [95% CI 2.30-3.90]/0.69 [95% CI 0.10-1.29] mmHg) compared with females. Reflecting increasingly higher BP levels with age, the pooled estimates of hypertension prevalence initially rose three-fold (from 10.6% [95% CI 8.2-13.0%] to 30.9% [95% CI 27.8-34.0%]) in those aged 21-30 to 41-50 years, and then two-fold to 66.4% (95% CI 64.2-68.7%) among those aged 71-80 years, respectively. Hypertension prevalence was lower in healthy weight [28.4% (95% CI 26.1-30.6%)] compared with overweight [35.8% (95% CI 31.4-40.1%)] adults. Regionally, prevalent hypertension was lowest in those living in Eastern Africa [27.2% (95% CI 24.8-29.7%)]. CONCLUSION: Our findings suggest a steep age-related pattern of increasing BP levels in the region that will adversely affect millions of people within the next 10-20 years without urgent intervention. A detailed review and analysis of 170 studies involving more than half a million adult men and women living in 26 sub-Saharan Africa countries, revealed that one in three have elevated blood pressure/hypertension.Elevated blood pressure levels, and the markedly increased risk of suffering a debilitating or fatal cardiovascular event at an early age, rose steeply from around one in ten affected at age 20–30 years to around one in three by the age of 50 years.Beyond the influence of age, the risk of having elevated blood pressure was different, given it increased markedly for overweight men and women, whilst those living in (mainly poorer) Eastern African countries had the lowest blood pressure levels.
16 May 2026
Read appraisal →Journal of global health
Impact of travel time to health facilities on perinatal outcomes: a systematic review with narrative synthesis and meta-analysis
BACKGROUND: Evidence-based global guidance on safe travel time for small or sick newborns who require transfer to health facilities after birth is lacking. A two-hour threshold is frequently cited in low- and middle-income countries (LMICs), while 30 minutes is commonly used in high-income countries (HICs). Although these thresholds are widely referenced, their empirical basis and consistency across levels of newborn care and journey types have not been systematically examined. This study synthesises the evidence linking travel time and perinatal outcomes. METHODS: We conducted a systematic review with narrative synthesis and meta-analysis to assess the impact of travel time or distance (home-to-facility or interfacility) on stillbirth, perinatal mortality, and neonatal mortality. We searched Embase, MEDLINE, and Cochrane Central Register of Controlled Trials for published studies from 2014 to 2023. Given substantial methodological heterogeneity, we used narrative synthesis as the primary analytical approach and conducted random-effects meta-analyses where studies were sufficiently comparable (≥2 with similar definitions and outcome windows), pooling effect estimates for travel time thresholds of 30 minutes, 1 hour, or 2 hours and travel distances of 5, 10, and 15 km. We assessed bias using the Newcastle-Ottawa Scale for cohort and case-control studies. RESULTS: Of 8317 screened records, 166 were eligible for full-text review, with 37 studies meeting the inclusion criteria- All but two had low or moderate risk of bias. Most studies (n = 26) came from LMICs and documented higher perinatal survival with shorter journeys. Studies from HICs demonstrated lower out-of-hospital birth, lower morbidity, and lower mortality with shorter journeys though associations were weaker. Across the narrative synthesis, shorter travel times were consistently associated with better outcomes. Exploratory pooling suggested a greater than 3-fold higher odds of survival for interfacility journeys under 30 minutes (odds ratio (OR) = 3.25; 95% confidence interval (CI) = 1.90-5.57) and over 2-fold higher odds of survival for journeys from any location to hospitals at all thresholds (OR = 2.06; 95% CI = 1.60-2.65 for 2 hours; OR = 2.20; 95% CI = 1.46-3.33 for 1 hour; OR = 1.92; 95% CI = 1.10-3.34 for 30 minutes), though prediction intervals were wide, reflecting methodological and contextual diversity. CONCLUSIONS: We found that shorter journeys were associated with better perinatal outcomes, with the highest survival rates observed for journeys under 30 minutes to the hospital. Due to substantial contextual and methodological heterogeneity, pooled estimates should be interpreted as illustrative, rather than definitive. A travel time norm of 30 minutes or one hour is preferable to the two-hour threshold currently used in LMICs. To safeguard perinatal survival rates, any travel-time standard should be balanced with corresponding quality of care standards. REGISTRATION: PROSPERO: CRD42023460423.
16 May 2026
Read appraisal →Journal of global health
Global prevalence of underweight and overweight/obesity among migrant workers: a systematic review and meta-analysis
BACKGROUND: Migrant workers are increasingly recognised as a nutritionally vulnerable population due to unstable working conditions, disrupted food environments, and limited access to health services. However, global estimates of malnutrition in this group remain fragmented. We aimed to identify the global prevalence of underweight and overweight/obesity among migrant workers and identify key moderating factors. METHODS: We conducted a systematic review and meta-analysis following PRISMA guidelines. We searched seven databases without restrictions on language, region, or year of publication. Observational studies reporting the prevalence of underweight (body mass index (BMI) < 18.5 kg/m2) or overweight/obesity (BMI ≥ 25 kg/m2) among migrant workers were included. We calculated pooled prevalence estimates using generalised linear mixed models with random effects. We assessed heterogeneity with I2 and Cochran's Q statistics. Moderator analyses were conducted using meta-regression and subgroup comparisons. Further, we appraised study quality using the Joanna Briggs Institute tools, and assessed the certainty of the evidence using GRADE. RESULTS: We included 30 studies involving 135 404 migrant workers with a mean age of 32.3 years (standard deviation = 11.1). The pooled prevalence was 4.7% (95% confidence interval (CI) = 3.1, 6.9) for underweight and 43.7% (95% CI = 39.8, 47.6) for overweight/obesity, suggesting a substantial double burden of malnutrition. Underweight was more common among local migrants and in lower-middle-income settings, particularly in South Asia, whereas overweight/obesity was more common among international migrants, especially in high-income countries and in Europe and Central Asia. Moderator analyses identified female proportion, destination country or region, income level, and marital status as significant moderators for both outcomes. CONCLUSIONS: Migrant workers experience a substantial double burden of malnutrition, although the pattern varies across migration contexts. Undernutrition remains a concern in lower-income settings, whereas overweight and obesity are more common in high-income settings. Integrating nutrition-sensitive strategies into labour and migration health policies, including healthier food environments, routine nutritional screening, and culturally appropriate interventions, may help reduce health inequalities in this population. REGISTRATION: INPLASY: 202540030.
16 May 2026
Read appraisal →JMIR mHealth and uHealth
Engagement of Users in Digital Health Applications: Scoping Review
BACKGROUND: Mobile health (mHealth) uses mobile technology as a tool for prevention and health promotion. Research indicates that user engagement is crucial for effective mHealth interventions and improved health outcomes. However, many studies report low adoption rates, rapid decline after initial use, and a lack of acknowledgment of user implications in achieving outcomes. Thus, conceptualizing participation in mHealth is essential to identify key determinants for engaging users. OBJECTIVE: This scoping review aims to identify and characterize the attributes and definitions of user engagement in mHealth, examine engagement methods, and analyze barriers and facilitators influencing participation. METHODS: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, Scopus, Web of Science, and PubMed databases were searched for publications between 2000 and 2025 with a 2-stage selection process. RESULTS: Out of 2489 articles identified, 1416 were screened, and 52 met the inclusion criteria. Half were recently published in the last 5 years (2020-2025). Existing literature focused on digital interventions for specific populations and health topics. Analysis revealed four main perspectives on engagement in mHealth: (1) usage metrics, (2) subjective user experiences, (3) a hybrid approach that combines both, and (4) a goal-oriented perspective (behavior change or health outcomes). CONCLUSIONS: To understand the complexity and multifactorial nature of participation, it is relevant to conceptualize it as a dynamic mechanism enabling users to achieve their objectives. Both quantitative use and subjective user experience should be integrated to reach the optimal intervention dose. Recognizing users' evolving needs, uniqueness, and their socioenvironmental context interdependence, it is essential to involve users in all stages (design, implementation, and iterative evaluation of mHealth). Findings will inform an e-Delphi study to establish consensus on engagement criteria.
16 May 2026
Read appraisal →European heart journal
Artificial intelligence-based quantification of breast arterial calcifications to predict cardiovascular morbidity and mortality
BACKGROUND AND AIMS: Women are underdiagnosed and undertreated for cardiovascular disease (CVD). Automatic quantification of breast arterial calcification (BAC) on screening mammography can identify women at risk for CVD. This study aimed to determine whether artificial intelligence-based automatic quantification of BAC from screening mammograms predicts CVD and mortality beyond PREVENT scores in a large, racially diverse, multi-institutional population. METHODS: This retrospective cohort study included 123 762 women from two healthcare systems who had screening mammograms. Breast arterial calcification was quantified using a transformer-based neural network for segmentation. Breast arterial calcification severity was categorized as zero (0 mm2), mild (>0-10 mm2), moderate (>10-25 mm2), and severe (>25 mm2). Kaplan-Meier analysis, Cox proportional hazards, and Fine-Gray competing event models were used to examine the association between BAC and major adverse cardiovascular events (MACE). RESULTS: Breast arterial calcification was detected in 16.1% (internal cohort) and 20.6% (external cohort) of women and provided significant prognostic value incremental to the PREVENT score. In PREVENT adjusted models, a clear dose-response was observed. Compared with zero BAC, mild [internal: hazard ratio (HR) 1.32, 95% confidence interval (CI) 1.10-1.59; external: HR 1.28, 95% CI 1.17-1.39], moderate (internal: HR 1.75, 95% CI 1.23-2.50; external: HR 1.79, 95% CI 1.55-2.06), and severe BAC (internal: HR 3.29, 95% CI 2.15-5.05; external: HR 2.80, 95% CI 2.36-3.32) were all prognostic for any MACE. Each 1 mm2 increase in BAC conferred an additional 2%-3% risk for MACE (P < .001). CONCLUSIONS: Automatically quantified BAC is an independent predictor of MACE and mortality, adding prognostic value to the PREVENT score. This approach may provide an opportunistic cardiovascular risk assessment during routine mammography screening without additional radiation exposure to guide earlier and more effective preventive care for women.
16 May 2026
Read appraisal →Journal of affective disorders
Sex differences in cognitive function trajectories and influencing factors in older adults: A machine learning study based on CHARLS and HRS
BACKGROUND: Identify the influencing factors that respectively affect the differences in cognitive function trajectories between China and the United States, and explore the reasons for gender and transnational differences. METHODS: Five waves of data from the China Health and Retirement Longitudinal Study (CHARLS) and the Health and Retirement Study (HRS) were utilized, and Latent Class Growth Models (LCGMs) was employed to identify cognitive trajectories. The optimal machine learning (ML) model was adopted and the Boruta algorithm was used to screen the variables. The SHAP value is used to explain the ranking of feature importance. RESULTS: The XGBoost model performs best among the six ML models. Education was the top influencing factor across groups. Family factors mattered more in China, while U.S. medical and endowment insurance had stronger effects. Men were more affected by external social networks; women were influenced by family responsibilities and community environments. CONCLUSION: Differences were linked to public services, social roles, and traditional culture. These results support the development of tailored interventions targeting gender-specific and culture pathways at the individual, family, society and community levels, offering actionable insights for promoting cognitive health in aging populations globally.
16 May 2026
Read appraisal →Journal of affective disorders
Prediction models for longitudinal trajectories of depression and anxiety: a systematic review
BACKGROUND: Prediction of atypical health trajectories may enable early intervention. We systematically reviewed the existing literature on models for predicting longitudinal depression and/or anxiety trajectories. METHODS: MEDLINE, Embase and APA PsycINFO were searched (from inception to 31-Jan-2025). We included population-based studies of children and adults (aged 3-65 years). Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST-AI) tool. RESULTS: Seven of the nine included studies were in adult populations with a diagnosis of depression or anxiety at baseline; two focused on child and adolescent populations. Only one study included anxiety trajectories. Identified trajectories typically comprised three to four groups including: chronic/persistent-high, stable-low, increasing/worsening, and improved/remitted groups. Various supervised predictive modelling methods were used. The number of final predictors included in models ranged from three to 152. Family and own/personal psychiatric history were the most common predictors but were not always important for model performance. Models including more predictors did not always perform better. Overall risk of bias was high in all studies. No studies were externally validated and no studies assessed the clinical utility of models. CONCLUSION: This review highlights a need for robust, validated models that can forecast future risk of persistent or worsening anxiety and depression, especially in young people where early intervention is possible.
16 May 2026
Read appraisal →PloS one
Optimising supervised machine learning algorithms predicting cigarette cravings and lapses for a smoking cessation just-in-time adaptive intervention (JITAI).
This study aimed to optimise the balance between participant burden and algorithm performance for predicting high-risk moments in a smoking cessation just-in-time adaptive intervention (JITAI) by systematically varying ecological momentary assessment (EMA) prompt frequency, predictor count, and training data source. Thirty-seven participants completed 16 EMAs per day for the first 10 days of their smoking cessation attempt, reporting mood, context, behaviour, cravings, and smoking lapses. Random forest algorithms predicting lapses and cravings were evaluated in terms of F1-score and ROC-AUC via mixed effects models accounting for clustering within individuals. Performance across out-of-sample individuals ranged from excellent to poor but was, on average, modest. Lapse prediction outperformed craving prediction, particularly for ROC-AUC (Median F1-score: Lapses 0.436 [IQR 0.180-0.625], Cravings 0.400 [IQR 0.048-0.649]; Median ROC-AUC: Lapses 0.659 [IQR 0.514-0.809], Cravings 0.628 [IQR: 0.510-0.729]). A substantial proportion of configurations fell below commonly used minimum performance thresholds, particularly for F1-score. Reducing EMA frequency had outcome- and metric-dependent effects. Lapse F1-scores improved with fewer prompts (16 EMAs: 0.254 [IQR 0.081-0.500], 3 EMAs: 0.588 [IQR 0.353-0.667]), while ROC-AUC showed a slight, inconsistent decline (16 EMAs: 0.661 [IQR 0.520-876], 4 EMAs: 0.613 [IQR 0.494-0.786], 3 EMAs: 0.704 [IQR 0.567-0.809]). For cravings, both metrics declined with fewer prompts (F1-score: 16 EMAs: 0.470 [IQR 0.141-0.745]; 3 EMAs: 0.333 [IQR 0.000-0.600]; ROC-AUC: 16 EMAs 0.700 [IQR 0.582-0.811], 3 EMAs 0.544 [IQR 0.421-0.676]). Feature reduction had negligible impact on lapse prediction (F1-score: all features 0.435, selected features 0.441; ROC-AUC: all 0.660, selected 0.657), but slightly reduced craving performance (F1-score: all 0.410 [IQR 0.117-0.646], selected 0.400 [IQR 0.000-0.650]; ROC-AUC: all 0.632, selected 0.622). Including participant-specific data improved lapse F1-scores (None 0.286 [IQR 0.000-0.571], 30 pc 0.542 [IQR: 0.329-0.667]), but not ROC-AUC (None 0.655 [IQR: 0.512-0.786], 30 pc 0.694 [IQR 0.513-0.852]); and impaired craving ROC-AUC (None 0.650 [IQR: 0.544-0.734], 30 pc 0.614 [IQR 0.493-0.730]; F1-score: None 0.424 [IQR 0.143-0.649], 30 pc 0.400 [IQR 0.000-0.703]). Overall, EMA-based machine learning detected lapse risk but showed modest overall performance and substantial inter-individual variability. Algorithms using higher EMA density, larger predictor sets, and participant-specific training data did not consistently outperform over more parsimonious approaches. However, machine learning prediction alone is unlikely to be sufficient for real-world JITAI implementation and may be best combined with complementary rules-based approaches.
16 May 2026
Read appraisal →PloS one
Data-driven differentiation analysis of urban high-tech industries: Research on bibliometrics and large language models.
This study examines inter-city heterogeneity in China's high-tech industries from a regional innovation systems (RIS) perspective, with a particular focus on how variations in knowledge production, technological application, and actor configurations are associated with divergent urban innovation trajectories. We compile more than 39,000 publications from the Web of Science (WOS) and nearly 10,000 patent records from the national patent database for the period 2016-2025, covering four representative cities-Wuhan, Chengdu, Hangzhou, and Tianjin-and four technological domains: artificial intelligence (AI), fiber-optic communication (FOC), intelligent connected vehicles (ICV), and storage chips (SC). The study develops an integrated analytical framework combining bibliometric analysis, co-word network modeling, collaboration network mapping, and large language model (LLM)-assisted semantic interpretation. LLMs are employed primarily in keyword cleaning, terminology standardization, and topic identification, improving the consistency and interpretability of textual metadata. Visualizations generated using VOSviewer highlight pronounced inter-city differences in technological portfolios, research priorities, and collaboration structures. The results suggest distinct urban innovation configurations across the four cities. Wuhan exhibits strong positioning in FOC and SC, reflecting a combined industry-academy orientation. Hangzhou shows high frontier intensity in AI and ICV, consistent with an industry-led and digitally driven innovation profile. Chengdu demonstrates substantial academic output but comparatively weaker evidence of technological translation, while Tianjin, despite a smaller overall scale, displays notable specialization in applied domains such as brain-computer interfaces and smart port technologies. Rather than replacing quantitative analysis, LLM-assisted interpretation supports the identification and contextualization of these patterns by enhancing semantic coherence and reducing noise in large-scale textual data. Overall, the proposed framework provides a reproducible and scalable approach for examining regional technological differentiation and is applicable to comparative studies of urban innovation systems across different regions and industrial contexts.
16 May 2026
Read appraisal →The British journal of general practice : the journal of the Royal College of General Practitioners
Does recommending healthy diets in general practice benefit secondary prevention of cardiovascular disease? A systematic review and meta-analysis.
BACKGROUND: Suboptimal diet is the main preventable risk factor globally for cardiovascular disease (CVD), posing major burden for primary care. However, healthy dietary recommendations' evidence in patients with established CVD is unclear. AIM: Systematically review and meta-analyse dietary patterns' effect on CVD patients' all-cause and CVD mortality, and CVD recurrence. METHOD: Publication databases were searched for randomised controlled trials (RCTs) (≥6 months follow-up) and prospective cohort studies. Random-effects meta-analysis calculated relative-risks (RR) and 95% confidence-intervals (95% CI). Cochrane bias risk tools assessed study quality. RESULTS: Screening 28 291 abstracts identified 41 articles meeting inclusion criteria. Nineteen articles from 14 unique RCTs conducted 1956-2020, enrolling 14 065 CVD patients, compared fat-replacement, Mediterranean, low-fat, low-sodium, and high-fibre diets with minimal/no dietary advice. Pooled results showed no diet intervention significantly impacted mortality/CVD outcomes. However, stratified meta-analysis revealed a Mediterranean-diet significantly reduced CVD mortality (RR: 0.40; 95% CI: 0.19, 0.83). Twenty-two cohort studies, conducted 1976-2017 for 104 386 CVD patients, predominantly assessed a Mediterranean diet (60%), showing greatest healthy dietary pattern adherence significantly reduced all-cause mortality by 29% (0.71; 0.65, 0.78), CVD mortality by 25% (0.75; 0.66, 0.84), and CVD recurrence by 17% (0.83; 0.75, 0.92). Overall, there was considerable between-study heterogeneity (RCTs: I2 = 34-60%, cohorts: I2 = 49-76%) partly explained by disparate geographical locations, and studies were mainly classified as of some concerns (65% RCTs) or high bias risk (52% cohorts). CONCLUSION: GPs providing healthy dietary advice, particularly the Mediterranean diet, likely enhances CVD secondary prevention. However, cogent studies with clearly defined diets are required to bolster the evidence.
16 May 2026
Read appraisal →Journal of affective disorders
Sociodemographic and clinical predictors of digital mental health intervention engagement among treatment-seeking psychiatric outpatients
BACKGROUND: Digital mental health interventions (DMHIs) have shown promise improving depression, anxiety, and psychiatric distress, yet real-world engagement remains low. Increasing engagement has great potential to improve the impact of DMHIs, but little is known about the drivers of engagement in naturalistic settings. To better understand predictors of engagement, we examined sociodemographic and clinical characteristics associated with DMHI usage among a large clinical sample of adults. METHOD: 1223 adults (74% White, 68% women, Mage = 36.8 years) with scheduled intake appointments for outpatient psychiatric services were randomized to either a mindfulness-based app (Headspace) or a CBT-based app (SilverCloud). Usage data were automatically collected, and participants were neither required nor compensated to use the apps. RESULTS: Participants engaged with their assigned DMHIs a median of 8 days, with 88.2% of participants using their assigned DMHI at least once. Participants engaged with Headspace for more than twice as many days [IRR (95% CI) = 2.4 (2.1, 2.7)] as SilverCloud. Female sex, white race, a college degree, and older age up to 60 predicted greater engagement. Further, depression severity was associated with engagement in a non-linear manner for those assigned to Headspace, with less engagement at minimal/mild and severe symptoms compared to moderate and moderately-severe symptoms. CONCLUSIONS: These findings indicate meaningful differences in engagement between DMHIs based on sociodemographic and clinical characteristics. There may be opportunities to improve engagement by tailoring DMHI offerings, with a particular emphasis on meeting the needs of less-engaged populations.
16 May 2026
Read appraisal →BMJ open
Transitioning from paper-based to electronic health management information systems in Africa: a scoping review protocol
INTRODUCTION: The rising shift from paper-based to electronic health management information systems (EHMIS) among global health systems has shown promising strides over the past decade. Yet, most African health systems have continued to use paper records with attendant gaps and challenges. Most African governments have now started transitioning from paper to EHMIS but lack adequate guidance to support this shift. There is therefore a need for harmonised regional guidance to ensure that such transitions are carried out systematically and take into account country-specific contexts. OBJECTIVE: The objective of this study protocol is to conduct a scoping review to generate evidence that will inform the development of a comprehensive guide to support countries in the WHO African Region in transitioning from paper-based to EHMIS. METHODS AND ANALYSIS: The review will follow established methodological guidance for scoping reviews as outlined by Arksey and O'Malley and further refined by Levac et al and the Joanna Briggs Institute, with reporting guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. A search strategy will be developed to systematically identify relevant studies from both published and grey literature sources including PubMed, Cochrane Library, Scopus and African Index Medicus. Other sources will include Google Scholar, Emerald Journal, the WHO Regional Office for Africa Library and websites of WHO, ITU and Ministries of Health. Reference lists of the retrieved published articles will be manually searched to identify additional relevant studies. Descriptive qualitative content analysis will be undertaken using the policy analysis framework and key findings will be summarised and presented using tables, charts and maps. ETHICS AND DISSEMINATION: This study does not involve the collection of primary data; therefore, ethical approval will not be required. On completion of the study, findings will be submitted for publication in a peer-reviewed scientific journal and will also be presented at national, regional and international conferences to support knowledge sharing and policy engagement.
16 May 2026
Read appraisal →JMIR mental health
Adoption of Digital Mental Health Interventions in National Health Service England, Scotland, and Wales: Freedom of Information Questionnaire Study
BACKGROUND: Digital mental health interventions (DMHIs) have been widely promoted to improve access to mental health care within the UK National Health Service (NHS), particularly following the COVID-19 pandemic. In 2015, a total of 48 technologies were reportedly used in NHS services in England, but over the past decade, substantial changes to regulatory requirements, evidence standards, and procurement processes have reshaped the digital mental health landscape. There is limited clarity regarding which DMHIs are currently being formally procured and funded by NHS mental health services across the United Kingdom. OBJECTIVE: This study aimed to identify and describe the DMHIs currently procured, contracted, or paid for by NHS mental health service providers in England, Scotland, and Wales for adult common mental health problems and to compare current procurement practices with findings reported in 2015. METHODS: Freedom of Information requests were submitted to all NHS mental health trusts in England and all health boards in Scotland and Wales. Responses were collated and screened to provide an updated and extended record of which technologies are reportedly procured or paid for by services. RESULTS: In total, 19 different DMHIs were identified as being procured across mental health service providers for adult common mental health problems at the time of data collection. This demonstrates a substantial reduction in the number of technologies being adopted into practice compared to the 48 reported in England in 2015. The findings reveal several key insights, including that only 2 technologies have remained in use for a decade, and they shed light on the types of technologies being selected and the variations in procurement practices among the 3 national health services. CONCLUSIONS: Despite the expansion of the digital mental health marketplace, the number of DMHIs formally procured by NHS mental health services has markedly decreased over the past decade. This consolidation may reflect increased selectivity and the adoption of higher-quality products, driven by strengthened regulatory oversight, evidence standards, and national guidance. Although these developments may enhance safety and quality assurance, they also raise important questions about innovation, market sustainability, and equitable access to digital mental health care. Ongoing monitoring of procurement practices is needed to inform policy, service design, and the future development of DMHIs.
16 May 2026
Read appraisal →Current allergy and asthma reports
Pharmacotherapeutic Medication Adherence in Patients With Allergic Rhinitis: A Systematic Review and Meta-Analysis
PURPOSE OF REVIEW: Medication adherence is essential for effective management of allergic rhinitis (AR), yet real-world adherence to guideline-recommended pharmacotherapies remains poorly characterized. This systematic review and meta-analysis aims to estimate pooled adherence proportions to prescribed intranasal corticosteroids and oral antihistamines in adults with AR, further stratified by adherence measurement method and geographic region. RECENT FINDINGS: Twelve studies encompassing 191,103 AR patients were included. Overall pooled adherence to both intranasal corticosteroids and oral antihistamines was 43%, with substantial heterogeneity across studies. Adherence estimates differed significantly by measurement method with self-reported adherence consistently exceeding pharmacy refill-based estimates for both medication classes. Significant geographic variation was also observed, with intranasal corticosteroid adherence ranging from 17% in North America to 61% in Asia, and oral antihistamine adherence ranging from 26% in North America to 48% in Northern and Western Europe. Peters' test did not indicate any significant publication bias and a Leave-One-Out (LOO) sensitivity analysis showed that no single study had a disproportionate effect on the overall effect size. Adherence to pharmacotherapy in AR is suboptimal, highly method-dependent, and varies significantly across geographic regions. These findings suggest that reported adherence rates are not only influenced by patients' behaviour, but also by the methods used to measure adherence and the broader healthcare environment. Integrating methodological rigour with geographic stratification provides more informative benchmarks for clinical practice and highlights the need for context-sensitive strategies to improve real-world AR management. Future research should prioritize standardized adherence measurement and prospective studies in underrepresented regions.
15 May 2026
Read appraisal →Journal of affective disorders
Machine learning and SHAP-based interpretation of dietary antioxidants' impact on comorbid MDD and suicidal ideation.
OBJECTIVE: To develop and validate a machine learning model for predicting major depressive disorder (MDD) with suicidal ideation (SI) by incorporating dietary antioxidants, and to elucidate the specific contribution of these antioxidants in the prediction. METHODS: Data were obtained from NHANES 2007-2010. Dietary antioxidants, including vitamins, minerals, and polyphenols, were the primary predictors. Demographic, lifestyle, and health-related variables were also included. Collinear variables were removed, class imbalance was corrected, and data were normalized prior to modeling. Twelve machine learning algorithms were compared using a systematic benchmarking protocol within the sklearn framework: Random Forest (RF), LightGBM, AdaBoost, XGBoost, Extra Trees, CatBoost, Gradient Boosting Decision Trees, Support Vector Machine, Decision Tree, Gaussian Naïve Bayes, Stochastic Gradient Descent, and K-Nearest Neighbors. SHapley Additive exPlanation (SHAP) values were calculated to interpret feature contributions within the best-performing model. RESULTS: A total of 9306 participants were included, of whom 247 with MDD comorbid with SI. After preprocessing, 31 dietary antioxidants and 9 demographic and health-related variables were retained for modeling. The RF classifier achieved the highest performance with an accuracy of 83%, precision of 0.825, recall of 0.838, area under the ROC curve of 0.927, and F1 score of 0.831. SHAP analysis identified vitamin C, kaempferol, myricetin, peonidin, luteolin, eriodictyol, hesperetin, pelargonidin, and zinc as the most influential predictors. CONCLUSION: The RF model exhibited superior predictive capability for comorbid MDD and SI. SHAP analysis highlighted the critical roles of dietary antioxidants, particularly vitamin C and kaempferol, in predicting these outcomes.
15 May 2026
Read appraisal →Journal of medical Internet research
Machine Learning and Deep Learning Models for Predicting Future Falls in Community-Dwelling Older Adults: Systematic Review and Meta-Analysis of Longitudinal Evidence
BACKGROUND: Machine learning (ML) and deep learning (DL) show promise for fall risk prediction, but prior reviews focused mainly on real-time fall detection, in-hospital falls, or conventional statistical models. The performance of ML-DL-based models for predicting future falls in community-dwelling older adults remains unclear. OBJECTIVE: This study aimed to review ML-DL studies for predicting future falls among community-dwelling older adults and meta-analyze discrimination where feasible. METHODS: Six databases were searched from inception to September 23, 2024, with updates on August 31, 2025, and February 28, 2026. We included longitudinal studies developing or validating ML-DL models to predict future falls in community-dwelling adults aged ≥60 years and excluded real-time detection, simulated or no fall, and inpatient studies. Risk of bias was assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Areas under the curve (AUCs) were meta-analyzed using Hartung-Knapp-Sidik-Jonkman random-effects models with 95% CIs. Heterogeneity, 95% prediction intervals (PIs), sensitivity analyses, and subgroup analyses were conducted. RESULTS: After screening 10,253 records, 28 (0.3%) studies were included; 18 (64.3%) focused on general older adults. Prediction horizons ranged from 3 months to 7 years, and fall incidence ranged from 1.6% to 46.6%. Twenty-three (82.1%) studies applied ML, and 5 (17.9%) studies used DL. Input modalities included text (n=18, 64.3%), sensor (n=5, 17.9%), image (n=1, 3.6%), and multimodal data (n=4, 14.3%). Common predictors included age, sex, fall history, depression, and basic daily activities. Only one model underwent external validation. Calibration reporting was sparse. All models were rated at high risk of bias. Ten models were meta-analyzed, yielding a pooled AUC of 0.79 (95% CI 0.69-0.87) with extreme heterogeneity (τ2=0.64; τ=0.80; I2=99.8%; Q=4128.99). The confidence-distribution bootstrap PI was 0.20 to 0.99, indicating substantial uncertainty in expected performance across new populations. Subgroup analyses indicated moderation by sample size and population type, with higher discrimination in specific populations than in general samples; however, the specific population subgroup included only 2 studies. Although all participants were community dwelling, some cohorts were recruited through clinically enriched pathways rather than general community sampling. CONCLUSIONS: ML-DL models show potential for identifying community-dwelling older adults at elevated future fall risk; however, wide PIs, limited external validation, and high risk of bias suggest real-world performance may be optimistic. The pooled AUC should be interpreted as a summary of reported discrimination under study-specific conditions, predominantly from internally validated, high-risk-of-bias models, rather than as a robust estimate of transportable real-world performance. This review extends prior reviews by focusing on community-dwelling settings and by integrating PROBAST, Hartung-Knapp-Sidik-Jonkman meta-analysis, PIs, and modality-specific synthesis to evaluate both discrimination and uncertainty. Findings support the use of ML-DL models for proactive fall prevention while emphasizing the need for validation and context-specific implementation.
15 May 2026
Read appraisal →BMJ mental health
Emulated trial of artificial intelligence use and subsequent depressive outcomes in a survey of US adults
BACKGROUND: Generative artificial intelligence (AI) use has been suggested to have adverse mental health consequences but a causal relationship has not been examined. OBJECTIVE: To simulate a randomised controlled trial of AI use in a work, school or personal context by applying target trial emulation to multiple waves of data from a nationally representative survey. METHODS: We conducted a target trial emulation using non-probability survey data from three waves of a nationally representative survey conducted between 18 June 2024 and 8 January 2025. Participants aged ≥18 years reported generative AI use frequency at baseline. High-frequency use was defined as multiple times per week or more. The primary outcome was depressive symptom severity measured using the Patient Health Questionnaire 9-item (PHQ-9) at follow-up. Generalised causal forests assessed heterogeneity of treatment effects. FINDINGS: Among 19 099 participants assessed at baseline, 2862 (15.0%) reported AI use at least multiple times per week. A subset of 3109 (16.3%) returned for follow-up. In the primary weighted analysis, high-frequency use was not significantly associated with change in PHQ-9 score at follow-up (mean difference -0.18, 95% CI -0.94 to 0.59; p=0.65). Multiple sensitivity analyses using alternate outcome definitions also did not identify significant causal effects. Generalised causal forests yielded no significant evidence of heterogeneity of effect (p=0.81). CONCLUSIONS: In an emulated randomised trial among US adults, generative AI use was not associated with subsequent depressive symptoms. This result does not support the premise that AI use causes greater depressive symptoms, although adverse outcomes among vulnerable individuals cannot be excluded. CLINICAL IMPLICATIONS: AI use is unlikely to cause increased depressive symptoms among most US adults. Continued monitoring should clarify potential risks among vulnerable populations.
15 May 2026
Read appraisal →BMJ open
Prevalence of anxiety and depression in adults who are high users of healthcare services and magnitude of associated costs: a systematic review
OBJECTIVES: Anxiety and depression are common and associated with higher use of general healthcare services. The aims of this systematic review were to (1) estimate the prevalence of anxiety and depression in adults who are high or costly users of general healthcare services in comparison to routine users and (2) estimate the magnitude of healthcare costs associated with the presence of anxiety and depression. DESIGN: Systematic review of the available literature. DATA SOURCES: MEDLINE, PsycINFO, EMBASE, CINAHL, PROSPERO and Cochrane Library were systematically searched without language restriction from inception to 1 April 2019 and updated on 25 October 2022, 16 October 2024 and 18 February 2026. ELIGIBILITY CRITERIA: Eligible studies described adults aged ≥18 years who were defined as high or costly general healthcare users and where the prevalence and/or associated costs of anxiety and/or depression were quantified. DATA EXTRACTION AND SYNTHESIS: Three reviewers independently extracted information on study characteristics, exposure and outcomes. RESULTS: From the 38 412 identified articles, 27 studies from 10 countries (in Europe, North America and Asia) involving 6 145 907 participants met eligibility criteria and were included. There were wide variations in the estimated prevalence of anxiety (3.8-67.2%) and depression (4.7-77.9%) among high healthcare users. The prevalence of both disorders was higher among high healthcare users than routine users in all studies with non-high user comparator groups. Only four studies investigated healthcare costs associated with depression. These uniformly reported that general healthcare costs are higher for those with depression than those without. No studies investigated costs associated with anxiety. CONCLUSIONS: Anxiety and depression are over-represented among high or costly healthcare users, although accurate quantification of the magnitude of difference is precluded by significant methodological heterogeneity and variability in definitions used. Improved identification of covert mental health problems is essential for the provision of effective interventions for patients and healthcare expenditure reduction. Future research should prioritise a standardised approach, with agreed definitions for high and/or costly healthcare use in different contexts. PROSPERO REGISTRATION NUMBER: CRD42018102628.
15 May 2026
Read appraisal →The New England journal of medicine
Ensitrelvir for Covid-19 Postexposure Prophylaxis in Household Contacts
BACKGROUND: Ensitrelvir, an oral inhibitor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3C-like protease, is approved in Japan for the treatment of mild-to-moderate coronavirus disease 2019 (Covid-19). Previously, no antiviral agents were approved for postexposure prophylaxis in household contacts of patients with Covid-19. METHODS: In this double-blind, randomized, placebo-controlled trial, we randomly assigned persons who were SARS-CoV-2-negative on local diagnostic testing but were household contacts of a patient with Covid-19 (the index patient) to receive either ensitrelvir (375 mg on day 1 and 125 mg daily on days 2 through 5) or placebo within 72 hours after symptom onset in the index patient. The primary end point was Covid-19 (defined by a central laboratory-confirmed positive reverse-transcriptase-polymerase-chain-reaction assay and the presence of ≥1 of 14 prespecified Covid-19 symptoms lasting ≥48 hours) by day 10 in a household contact in the modified intention-to-treat population (all the participants who underwent randomization, had a central laboratory-confirmed negative RT-PCR test for SARS-CoV-2 at baseline, and received at least one dose of the trial drug or placebo). RESULTS: The modified intention-to-treat population included 1030 participants in the ensitrelvir group and 1011 in the placebo group. The mean age of the participants was 42.4 years; 71.1% had undergone randomization within 48 hours after symptom onset in the index patient, and 37.0% had at least one risk factor for severe Covid-19. The incidence of Covid-19 was lower in the ensitrelvir group than in the placebo group (2.9% vs. 9.0%; risk ratio, 0.33; 95% confidence interval [CI], 0.22 to 0.49; P<0.001). The incidence of adverse events during the trial was similar in the two groups (15.1% in the ensitrelvir group and 15.5% in the placebo group), as was the incidence of serious adverse events (0.2% in each group). No Covid-19-related hospitalizations or deaths were reported. CONCLUSIONS: Ensitrelvir administered to household contacts of a patient with Covid-19 within 72 hours after symptom onset in the index patient was effective in preventing Covid-19 in the contacts. (Funded by Shionogi; SCORPIO-PEP Japan Registry for Clinical Trials number, jRCT2031230124; ClinicalTrials.gov number, NCT05897541.).
15 May 2026
Read appraisal →PloS one
Health related quality of life among hypertensive adults living in rural Vietnam: Results from a cluster-randomised controlled trial
BACKGROUND: There is a growing burden of hypertension (HTN) among adults living in rural Vietnam, which is associated with reduced health related quality of life (HRQoL). Few community-based interventions have, however, attempted to improve the quality of life in patients with uncontrolled HTN. This study aimed to examine the impact of a multi-component intervention on HRQoL in adults with uncontrolled HTN. METHODS: This cluster-randomized controlled trial was conducted in sixteen communities (8 intervention and 8 comparison) living in a rural setting in Vietnam (2017-2022). Consenting adults with uncontrolled HTN were enrolled. The comparison arm received training sessions about HTN prevention and management and patient education materials. The intervention arm received information similar to the comparison group and three enhancement components, namely a storytelling intervention, home blood pressure (BP) self-monitoring, and expanded community health worker services. The primary outcome was the differential change in HRQoL over 12-month follow-up period, measured using the 12-Item Short Form Health Survey (SF-12), which generates a Physical Component Summary (PCS-12) and a Mental Component Summary (MCS-12). The total HRQoL score was calculated as the sum of PCS-12 and MCS-12, with higher scores indicating better HRQoL. RESULTS: A total of 671 patients were studied; their mean age was 66 years and 55% were women. At the 12-month follow-up, the intervention group showed a significant increase in their PCS-12 with a multivariable-adjusted difference of 4.2 points (95% CI: 2.0-6.4) compared with the control group. While the MCS-12 scores increased for both groups, their differential change over 12 months was not statistically significant (multivariable-adjusted difference: 1.4 points; 95% CI: -0.6; 3.5). CONCLUSION: Our results demonstrate that a multicomponent intervention effectively improved overall HRQoL with a significant impact on physical health-related HRQoL in individuals with uncontrolled HTN. TRIAL REGISTRATION: ClinicalTrials.gov, Registration number: https://clinicaltrials.gov/study/NCT03590691, (registration date July 17, 2018).
15 May 2026
Read appraisal →Journal of medical Internet research
Leveraging Text Messaging and Behavior Theory to Improve Colorectal Cancer Screening in Federally Qualified Health Centers: Cohort Study
BACKGROUND: Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States. Despite recommendations for screening to begin at the age of 45 years, significant disparities persist, particularly among medically underserved populations. OBJECTIVE: This study examines the effectiveness of SMS text messaging reminders in improving CRC screening rates across 2 large federally qualified health centers (FQHCs) serving vulnerable populations. METHODS: The study included 4822 adults aged ≥45 years, receiving care at 2 large FQHC networks in Texas and California. Participants were assigned to one of four groups: (1) control (no SMS text messages), (2) single-outreach SMS text overdue message, (3) three-week SMS overdue and reminder text messages, and (4) six-week SMS text messages that were informed by behavior theory. Data were collected from May 2023 to July 2024. The outcome measure was a binary indicator of whether the participant underwent 1 of 3 CRC tests, fecal immunochemical test, colonoscopy, and Cologuard, within 90 days of completing the SMS text messaging reminders. Independent variables included demographic, geographic, clinical, and primary care access variables. Multivariate logistic regression models were used to examine associations between CRC screening completion and the SMS text messaging reminder groups, adjusting for covariates. Adjusted odds ratios (aORs) and 95% CIs were reported. RESULTS: In the combined 3-test model, patients in the single-outreach SMS text message (aOR 1.22, 95% CI 1.00-1.47) and the 3-week SMS text message (aOR 1.27, 95% CI 1.05-1.53) groups had higher odds of completing the screening test compared to those in the control group. Within the fecal immunochemical test-only model, patients in the 3-week SMS text message group (aOR 1.25, 95% CI 1.00-1.56) were more likely to complete the screening test. Within the Cologuard-only model, patients in the 3-week SMS text message group (aOR 7.01, 95% CI 1.96-25.07) and the 6-week SMS text message group (aOR 5.75, 95% CI 1.53-21.61) had significantly higher odds of CRC screening completion. CONCLUSIONS: The findings highlight that moderate-frequency SMS text messaging reminders can effectively increase CRC screening rates in FQHCs; however, critical factors include the timing and frequency of these reminders. The 3-week intervention was associated with improved screening uptake, whereas the 6-week theory-informed intervention did not demonstrate a significant advantage over the control group, potentially reflecting a ceiling effect or message fatigue associated with more frequent messaging. Additionally, the study highlights unique screening patterns that contradict previous literature, underscoring the importance of a tailored approach for vulnerable communities.
15 May 2026
Read appraisal →JMIR aging
Leveraging Multimodal Large Language Models for Fall Risk Reduction in Older Adults in the Home: Proposed Model Design
This research letter proposes a novel model design leveraging natively multimodal large language models to identify fall risks and generate visualizations of recommended home environmental modifications, aiming to improve the accessibility and impact of personalized fall prevention advice for older adults. Through a pilot rating study, this work demonstrates that multimodal large language models can generate safe and actionable advice to reduce fall risk in lived spaces of older adults, and also generate realistic edits based on original images. While this concept needs further testing and clinical comparison, it highlights a promising avenue for further innovation of fall prevention tactics.
15 May 2026
Read appraisal →PloS one
The impact of walking on creative thinking: A systematic review and meta-analysis
BACKGROUND: Walking is associated with many benefits, from improved mental health to a reduced risk of mortality - but can it boost creative thinking? Current evidence suggests a positive effect of physical activity on creative thinking, but the specific effect of walking has not been adequately explored. METHODS: We conducted a systematic search of the PsycINFO, MEDLINE, Scopus, and ProQuest databases from inception to 8 January 2025 using search terms related to walking and creativity. We then performed meta-analyses of Cohen's d effect sizes to assess the effect of walking on creative thinking, as represented by divergent thinking (the ability to generate novel and useful ideas) and convergent thinking (the ability to analyze and select ideas to find the best solution). We assessed study quality using a creativity-specific tool, and the certainty of the evidence with the Grading of Recommendations Assessment, Development and Evaluation Framework. RESULTS: We identified 23 studies (12 randomized experimental studies, nine non-randomized experimental studies, two observational studies) from 16 articles including a total of 1,036 participants, most of whom were post-secondary students. We found moderate certainty evidence of a large effect of walking on divergent thinking (d = 0.93 [95% CI 0.44, 1.42]), and very uncertain evidence of a null effect of walking on convergent thinking (d = 0.16 [95% CI -0.31, 0.63]). Sensitivity analyses of randomized trials only found similarly large effects of walking on divergent thinking ability (d = 0.82 [95% CI 0.35, 1.28]). CONCLUSION: Results suggest that walking likely results in a large increase in divergent thinking, indicating its potential as an intervention to stimulate creative idea generation.
15 May 2026
Read appraisal →Journal of agricultural and food chemistry
Serum-Free Media in Cellular Agriculture: Current Challenges, Design Strategies, and Future Prospects
Cellular agriculture (CA), an emerging and sustainable agricultural paradigm, offers a promising solution to global challenges in food security and environmental sustainability. However, the large-scale manufacturing of CA is hindered by its dependence on serum-based culture media, which are costly and compositionally variable and raise biosafety and animal welfare concerns. Addressing this bottleneck requires the development of affordable, reliable, and ethically compliant serum-free media (SFM). This perspective elucidates the functional roles of serum components, summarizes recent advances in serum substitutes, and highlights microorganism-derived substitutes as particularly promising because of their low cost, compositional stability, and scalability. Furthermore, we outline the evolution of SFM formulation from empirical and design-of-experiment-based optimization to multiomics-driven formulation and artificial intelligence (AI)-assisted design. Overall, this review provides a focused framework for understanding current challenges, design strategies, and future directions of SFM development for CA.
15 May 2026
Read appraisal →Blood advances
Novel use of a hash-based tokenization for sharing sickle cell disease data without sharing protected health information
Efforts to improve care for people living with sickle cell disease (SCD) have led to the development of several registries; however, many are dependent on time-limited funding and lack coordination. Consequently, existing data sets are fragmented and do not provide the comprehensive, longitudinal insights achievable through well-integrated registries. Although relevant data exist within electronic medical records across institutions, aggregation is limited by poor interoperability, inconsistent use of common data elements, and poor translation of natural language into codified data. These barriers hinder population-level research and contribute to gaps in understanding the lifelong progression of SCD. Creating a new common data system risk losing years of valuable data, highlighting the need to optimize existing data resources. This study aimed to develop a privacy-preserving method to securely link 3 of the largest SCD data collection efforts in the United States. Conducted at the University of Alabama at Birmingham Lifespan Sickle Cell Center, the study leveraged institutional review board-approved access to the Sickle Cell Data Collection project, the American Society of Hematology Research Collaborative Data Hub, and the Globin Research Network for Data and Discovery. Identity tokens were generated and hashed using Secure Hash Algorithm (SHA)-256 to enable secure linkage without sharing protected health information. A total of 8026 records were identified across the 3 registries. Deterministic matching of hashed tokens identified 1080 unique individuals appearing in at least 2 data sets. This study demonstrates the first privacy-preserving linkage of multiple SCD registries. Secure data integration enhances interoperability and enables richer longitudinal analyses critical for advancing SCD research and treatment development.
15 May 2026
Read appraisal →Journal of medical Internet research
Plain Language Summarization of Environmental Health Research Using Generative AI: Community-Engaged Qualitative Study
BACKGROUND: Plain language summaries (PLSs) are increasingly required in environmental health publications to improve public accessibility. Generative artificial intelligence (AI) systems such as large language models can automatically produce such summaries; however, automated summaries often overlook local context and cultural relevance-limitations that are critical in environmental health research, where affected communities face disproportionate exposure and health risks. OBJECTIVE: This study aimed to develop and refine community-informed prompts for generating PLSs of environmental health research using generative AI. METHODS: We conducted a community-engaged qualitative study in Louisville, Kentucky, involving workshops with 97 participants from 4 stakeholder groups: summer interns at a local social justice nonprofit organization, participants in a youth development program, participants in a faith-based community organization, and members of a community advisory board focused on environmental justice. Participants reviewed PLSs generated using 3 different prompt styles in GPT-4o (ChatGPT, OpenAI). Feedback was collected through structured discussions and facilitator notes. Data were analyzed using thematic analysis informed by knowledge translation frameworks to identify preferred structural, linguistic, and contextual features of the summaries. RESULTS: Participants consistently preferred summaries between 300 and 400 words, written at a sixth- to eighth-grade reading level. Key priorities included presenting definitions before findings, using headings and bullet points to improve readability, and clearly explaining real-world and environmental justice implications. Narrative summaries without structure were viewed as overly long and difficult to interpret, while purely bullet-based formats were considered too simplified. Feedback from youth participants emphasized clarity and practical relevance, while faith-based participants highlighted the importance of trust and contextual framing. These insights informed the development of a community-refined prompt that included definitions, key findings, an introduction, and a concluding section on community implications. CONCLUSIONS: Community-engaged prompt development may improve the relevance and interpretability of AI-generated PLSs of environmental health research. Incorporating stakeholder perspectives into prompt design offers a replicable strategy for improving research translation and ensuring AI-generated summaries reflect the informational needs of affected communities.
15 May 2026
Read appraisal →Journal of cross-cultural gerontology
Mapping the Use of Information and Communication Technologies in Health Interventions for Older Adults: A Rapid Review
This rapid review mapped how information and communication technologies (ICTs), particularly digital health applications, are being used within healthcare services for adults aged 55 years and older. Following the Joanna Briggs Institute methodology and guided by the Population-Concept-Context framework, studies published between 2016 and 2024 were identified and reported in accordance with the PRISMA extension for scoping reviews, based on a previously published protocol registered on the Open Science Framework. Nineteen studies were included after critical appraisal. The findings indicate that ICT use is most frequently associated with improved accessibility and coordination of healthcare services, support for health professionals' training and care management practices, and positive health-related outcomes for older adults, particularly in the domains of mental health, social participation, and self-care. However, the evidence remains heterogeneous and often limited in its reporting of design and implementation processes, highlighting the need for further context-sensitive research that addresses ethical, equity, and implementation considerations in the use of digital health technologies for older populations.
14 May 2026
Read appraisal →Current pain and headache reports
Addressing the Treatment Gap for Pediatric Headache in Underserved Regions
PURPOSE OF REVIEW: This review explores innovative strategies to address the treatment gap for pediatric headache disorders in underserved regions worldwide. RECENT FINDINGS: Global Burden of Disease studies indicate that the fastest growth in pediatric headache burden occurs in low- and middle-income countries, where reported prevalence likely underestimates true disease burden due to healthcare access barriers. Telemedicine demonstrates comparable efficacy, safety, and satisfaction to in person care. Artificial intelligence based diagnostic models achieve high accuracy for pediatric migraine identification. School-based interventions leveraging existing educational infrastructure improve headache knowledge and coping behaviors. Task shifting and integrated care delivery models are increasingly recognized as essential components of sustainable care. Telemedicine, artificial intelligence, school-based interventions, task shifting, and integrated care networks represent scalable solutions for extending headache care to underserved pediatric populations. Realizing their potential requires integrating technological innovation with workforce capacity building, community engagement, and policy advocacy.
14 May 2026
Read appraisal →Current psychiatry reports
The Type of Providers Delivering Practice Elements Used in Child Mass Trauma Interventions: A Systematic Review
PURPOSE OF REVIEW: This review identified the relative frequency of use of various types of providers delivering practice elements in 130 child mass trauma interventions and compared the use of these providers across events, populations, and settings. RECENT FINDINGS: Mental health professionals (MHPs) more frequently delivered cognitive, self-monitoring, exposure, and narrative elements than other providers while non-specialist providers (NSPs) and teachers and school personnel (TSPs) delivered support networking and social skills training more frequently. MHPs administered interventions to targeted populations more frequently, and TSPs administered interventions to universal populations more frequently. Only MHPs administered interventions at clinical facilities; NSPs delivered a majority of interventions at community sites. Understanding the specific practice elements delivered by providers with different backgrounds and training can inform efforts to enhance the reach and impact of mass trauma services. Future publications should report greater detail about providers and their training and about specific practice elements used.
14 May 2026
Read appraisal →Annals of work exposures and health
Occupational mechanical exposures and upper-body musculoskeletal disorders: an overview of systematic reviews
OBJECTIVES: The aim was to provide a comprehensive overview of systematic reviews with meta-analyses of the association between occupational mechanical exposures and upper-body musculoskeletal disorders. METHODS: A systematic literature search was conducted in PubMed, Web of Science, Embase, and CINAHL. Systematic reviews were considered eligible if they included occupational mechanical exposures and provided weighted measures of association in relation to specific musculoskeletal disorders. From each systematic review, data on eg databases searched, exposure, outcome, effect estimates, and quality of evidence of the association were extracted. The methodological quality of each systematic review was assessed using AMSTAR 2. RESULTS: The screening of 1,756 articles resulted in the inclusion of 17 systematic reviews with meta-analysis covering 6 musculoskeletal disorders: subacromial pain syndrome (n = 3), lateral epicondylitis (n = 2), carpal tunnel syndrome (n = 7), Dupuytren's disease (n = 4), hand-arm vibration syndrome (n = 1), and hand osteoarthritis (n = 1). The weighted odds ratios from the meta-analyses generally ranged between 1.5 and 3.0. Approximately 35% of the included systematic reviews assessed the quality of evidence of the association, and among these, 48% graded the evidence as being low to very low. CONCLUSIONS: In general, this overview found an increased risk associated with most mechanical exposures in relation to specific upper-body musculoskeletal disorders. However, grading of evidence quality was rarely applied, and when present, showed substantial variability. Future research related to primary studies should prioritise high-quality prospective studies and objective exposure assessments, and systematic reviews would benefit from standardised methodologies and improved reporting transparency to further strengthen the evidence quality.
14 May 2026
Read appraisal →Sleep
Effects of a guided digital intervention on sleep and mental health outcomes in university students - a randomized controlled trial
STUDY OBJECTIVES: To evaluate the effectiveness of a guided digital intervention targeting sleep and circadian rhythms in university students. METHODS: We randomized 195 university students with self-reported insomnia (Insomnia Severity Index ≥10) from nine Dutch Universities to receive either the 5-week guided digital cognitive-behavioral therapy for insomnia "i-Sleep & BioClock", or digital sleep psychoeducation and sleep monitoring. Online assessments were at baseline, 3 (mid-treatment), 6 (post-treatment), and 18 (follow-up) weeks. The primary outcome was insomnia severity at 6 weeks. Secondary outcomes were symptoms of depression and anxiety; functioning; quality of life (QoL); academic performance; and sleep and light exposure diary outcomes. RESULTS: From Nov 1st 2023 until Sept 5th 2024, we randomly assigned 96 students (age 23.8 ± 3.8, 75.4% female) to the intervention and 99 to the control condition, stratified by university and gender. Fifty-one percent completed the post-treatment assessment, and 30% the follow-up. 31% were intervention completers. Linear mixed models showed no significant time x treatment interaction for insomnia severity ("i-Sleep & BioClock": baseline ISI M = 16.8, SD = 4.0; post-treatment ISI M = 10.2, SD = 3.9; Digital psychoeducation: baseline ISI M = 16.5, SD = 3.6; post-treatment ISI M = 11.1, SD = 4.2). The difference in change between groups was -1.17 points (95% CI -2.72 to 0.38), p=.14, Cohen's d = -0.31. Most secondary outcomes showed no significant time x treatment effects. CONCLUSIONS: "i-Sleep & BioClock" was not more effective than online psychoeducation on most outcomes, possibly due to active elements present in both conditions or low adherence. Future research should identify factors for early disengagement and investigate which intervention components drive improvements in sleep. CLINICAL TRIAL: Effectiveness of a Guided Self-help Intervention for Improving Sleep in University Students, https://clinicaltrials.gov/study/NCT06023693, prospectively registered at ClinicalTrials.gov on August 3rd, 2023.
14 May 2026
Read appraisal →JMIR aging
Self-Identified Age Cohorts and Personal Experience Sharing in Pseudonymous Online Spaces: Natural Language Processing Analysis of Reddit
BACKGROUND: While older adults' social media use has been widely studied for its instrumental benefits, such as accessing health information or maintaining family ties, research has largely focused on identity-based platforms that mirror offline social networks, leaving pseudonymous, interest-driven environments such as Reddit underexplored. Although older adults actively participate in these spaces to share personal narratives and engage beyond their existing social roles, the literature has yet to center their own voices, with most existing work focusing on caregivers or younger users discussing older adults rather than older adults speaking for themselves. OBJECTIVE: Integrating a life course perspective with the concept of subjective age cohort, this study examines how Reddit users who explicitly self-identify as being in their 50s, 60s, or 70s engage in self-expression and personal experience sharing within pseudonymous online spaces. METHODS: Using data collected via the Reddit application programming interface, this study analyzed posts and comments from 848 self-identified older Reddit users, including 488 future older adults in their 50s (57.5%) and 360 current older adults in their 60s and 70s (42.5%) identified through age-based flairs in the subreddit r/AskOldPeople. A fine-tuned large language model (BLOOM-560m; F1-score=0.96) classified 4,055,275 sentences into three personal experience domains: (1) health and wellness, (2) personal relationships and identity, and (3) professional and financial life. Chi-square analysis compared domain distributions across age groups. BERTopic topic modeling identified thematic patterns within each domain. RESULTS: Of 569,107 personal experience sentences identified, personal relationships and identity comprised the largest share (n=268,212, 47.1%), followed by professional and financial (n=186,768, 32.8%) and health and wellness (n=114,127, 20.1%). Chi-square analysis revealed significant between-group differences (χ22=34.7; P<.001): current older adults shared proportionally more about health and wellness, whereas future older adults shared more about relationships and identity. Topic modeling further revealed qualitatively distinct emphases within each domain. Future older adults' posts frequently discussed menopause, depression, and friendships, while current older adults more frequently addressed chronic illness, aging, and financial security. Both groups used pseudonymity to disclose sensitive or stigmatized topics. CONCLUSIONS: This study demonstrates that older adults' personal experience sharing on pseudonymous platforms is shaped by the simultaneous interplay of life course stage, age cohort background, and platform affordances, rather than by any single factor. Pseudonymous environments such as Reddit enable disclosures of health vulnerabilities, contested social identities, and emotional experiences that are structurally discouraged on identity-based networks, and this has direct implications for how digital inclusion is conceptualized and practiced. Beyond operational literacy, supporting older adults' expressive inclusion in interest-based, pseudonymous online communities represents a meaningful yet underaddressed dimension of digital participation policy.
14 May 2026
Read appraisal →BMJ open
Mapping the evidence on stillbirth prevention across the reproductive continuum: an umbrella review
OBJECTIVES: To collate and appraise evidence from existing systematic reviews and meta-analyses on interventions to prevent stillbirth and reduce perinatal mortality across the reproductive continuum, including preconception, antenatal, intrapartum and immediate newborn periods. DESIGN: Umbrella review synthesising evidence from systematic reviews, including meta-analyses where available. DATA SOURCES: A comprehensive search was conducted in CENTRAL (via Cochrane Register of Studies Online), PubMed, Embase and Web of Science, along with trial registries (WHO International Clinical Trials Registry Platform, ClinicalTrials.gov and ISRCTN Registry), from inception to 12 January 2026. ELIGIBILITY CRITERIA: Systematic reviews and meta-analyses synthesising randomised controlled trials or quasi-experimental studies that reported stillbirth, perinatal mortality, fetal loss or fetal death were included. Reviews focused exclusively on predefined high-risk populations were excluded. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently extracted data and assessed methodological quality using A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2). Grading of Recommendations, Assessment, Development and Evaluation (GRADE) certainty ratings were extracted as reported by the original review authors. Evidence synthesis followed a structured framework adapted from Ota et al, integrating direction of effect and certainty of evidence based on pooled estimates and GRADE assessments. Publication overlap was assessed using the Corrected Covered Area index where relevant. RESULTS: A total of 116 systematic reviews were included, synthesising evidence from randomised controlled and quasi-experimental studies across preconception, antenatal, intrapartum and immediate newborn periods. Evidence from individual reviews showed clear benefit for several interventions, including balanced energy-protein supplementation, home visits by community health workers, birth preparedness interventions, labour induction at or beyond 37 weeks of gestation and skilled or community-based intrapartum care, primarily for reducing perinatal mortality. Reduced antenatal visit schedules compared with standard care were associated with a possible increase in stillbirth or perinatal mortality, indicating potential harm. Many interventions-such as group antenatal care (ANC), nutritional education, case-note provision, routine ultrasound or Doppler monitoring, antibiotic treatment for bacterial vaginosis, antiretroviral therapy in pregnancy and several pharmacological or hormonal interventions-demonstrated unknown or inconclusive effects on stillbirth or perinatal mortality, largely due to imprecision and heterogeneity. CONCLUSIONS: This umbrella review identifies a range of interventions with evidence of effectiveness across the reproductive continuum, particularly those addressing maternal nutrition, continuity of ANC and quality intrapartum and newborn care. However, substantial evidence gaps remain, especially for interventions widely implemented without strong supporting evidence. These findings highlight the need for context-specific implementation research and prioritisation of proven strategies in low- and middle-income countries, where the burden of stillbirth remains highest. PROSPERO REGISTRATION NUMBER: CRD42024531100.
14 May 2026
Read appraisal →PloS one
Framing artificial intelligence in Chilean digital press before and after the launch of ChatGPT: From concern to optimism
This article examines the evolution of AI framing in Chilean national digital media before and after the launch of ChatGPT in 2022. Through topic modeling and emotion analysis of 1,466 articles published by six media outlets over periods that begin between 2000 and 2014, depending on the outlet, and extend in all cases until 2024, this study identifies significant thematic and affective changes. In the pre-ChatGPT period, coverage combined recognition of AI's capabilities with concerns regarding labor displacement, governance, and human identity, frequently referencing global corporations and state institutions. In the post-ChatGPT period, topics became narrower in scope, with fewer actors and greater emphasis on universities and cultural organizations implementing AI. The focus shifted from the development of AI systems to their applications, predominantly framed in positive terms. At the same time, negative sentiment was largely confined to epistemological uncertainty. This transformation aligns with national surveys indicating growing public optimism, diverges from Global North debates centered on regulation and privacy, and converges with East Asian framings that are oriented toward innovation and creativity. These findings suggest that the launch of ChatGPT coincided with a reinforcement of a socio-technical imaginary of AI as inevitable and beneficial, yet potentially limiting the diversity of public debate.
14 May 2026
Read appraisal →JMIR human factors
The Quality and Characteristics of Digital Mental Health Apps: Mixed Methods Study
BACKGROUND: There are around 20,000 mental health apps available in app stores. The Organisation for the Review of Care and Health Apps (ORCHA), a United Kingdom digital health compliance company, has assessed a number of digital mental health apps with regard to their quality, professional and clinical assurance, data privacy, and user experience. This study analyzes the data that were collected by ORCHA when they assessed mental health apps. OBJECTIVE: This study aimed to examine the characteristics of mental health apps regarding their quality, target users, features, underpinning evidence, and data privacy. METHODS: A dataset comprising ORCHA Baseline Review assessments of over 2000 digital health apps, including 436 mental health apps, was used. This study uses exploratory data analysis to gain insight into the quality and characteristics of mental health apps. Methods such as descriptive and inferential statistics, k-modes clustering, and association rule mining were used to explore the quality of mental health apps as well as reveal insights into the different cost types, target users, app features, data types, and evidence of app content. RESULTS: Information provision, data capture, and data sharing were the most common features within the 436 mental health apps. The examined apps primarily targeted the following groups: adults (n=229, 52.5%), everyone (n=184, 42.2%), and teens (n=135, 31%). The cost of apps has not been linked to the quality of mental health apps, although paid apps or apps with in-app purchases may include additional services. Indicated user acceptance or benefit is the most common type of evidence provided by these mental health apps. A total of 241 (55.3%) apps included a qualified professional in app development, and 251 (57.6%) apps provided evidence within the app that the developer validated any guidance with relevant reliable information sources or references. Usage data and email were the most commonly collected data types. Association rule mining showed that email, IP address, name, and usage data are often co-collected by the same apps. K-modes cluster analysis showed that mental health apps can be categorized into 2 clusters, where one cluster of apps (n=182, 41.7%) collected more data than apps in the other cluster. CONCLUSIONS: Mental health apps are commonly targeted for everyone to use, but many apps are targeted toward teens or adults. Our study suggests that many publicly available mental health apps did not take the precautions (such as the involvement of appropriate health professionals, literature references, or conducting tests) to ensure that their content is valid and research based. Greater effort on behalf of mental health app developers is needed to ensure that the public is provided with high-quality apps. Moreover, our study indicates that the mental health apps that collect more data tend to score better on the ORCHA Baseline Review assessment.
13 May 2026
Read appraisal →Oral health & preventive dentistry
Prevalence and Risk of Dental Erosion Linked to Carbonated Drinks in Adolescents: A Systematic Review and Meta-Analysis
PURPOSE: To determine the prevalence of dental erosion due to carbonated beverage consumption among adolescents and the association between both variables through a systematic review and meta-analysis. METHODS AND MATERIALS: This study was conducted in accordance with the preferred reporting items for systematic review and meta-analysis (PRISMA) guidelines for systematic reviews. A comprehensive literature search was performed in PubMed, Scopus, Web of Science, LILACS, and SciELO. Observational studies were included, and the PEO framework was used to identify dental erosion and non-erosion (outcome) and intake of carbonated beverages (exposure) in adolescents (population). The prevalence of dental erosion and odds ratio (OR) with 95% confidence interval (95%CI) to determine the risk of carbonated beverages were estimated with MedCalc V.23.0.2 and Review Manager (RevMan V.5.4.1) software, respectively. A P value 0.05 was considered to indicate statistical significance. RESULTS: A total of 24 studies met the eligibility criteria. The pooled sample included 21,541 adolescents, and the overall erosion prevalence was 37.6% (95%CI 26.3, 49.7%). The meta-analysis revealed a significant association between carbonated beverage consumption and dental erosion (OR = 1.98, 95%CI: 1.42-2.77; 7785 participants; I2 = 80%; P 0.0001). CONCLUSION: Dental erosion is a prevalent condition among adolescents, with a pooled prevalence of 37.6%. Carbonated beverage consumption among adolescents is associated with a 98% increased risk of dental erosion.
13 May 2026
Read appraisal →Lancet (London, England)
Impact of introducing RTS,S/AS01E malaria vaccine on mortality in young children in Ghana, Kenya, and Malawi: an observational evaluation of a cluster-randomised implementation programme
BACKGROUND: Malaria vaccines have been added to immunisation schedules in 25 sub-Saharan African countries, with the expectation that deaths in young children would be prevented. The introduction of the RTS,S/AS01E malaria vaccine (RTS,S) in Ghana, Kenya, and Malawi in 2019 was evaluated over 4 years to show the impact on mortality in young children and to monitor severe malaria admissions, vaccine uptake, and safety. Favourable evidence on safety and impact on severe malaria admissions during the first 2 years contributed to WHO's recommendations on malaria vaccines. Here, we report the primary analysis of the impact on mortality at 46 months. METHODS: Clusters of administrative units (districts in Ghana, subcounties in Kenya, and groups of immunisation clinics in Malawi), each with an estimated annual birth cohort of about 4000 children, were randomly assigned 1:1 to introduce the RTS,S malaria vaccine in 2019 (implementation areas), or to implement later (comparison areas). RTS,S was delivered in a four-dose schedule, at age 6, 7, 9, and 24 months in Ghana and Kenya, and at age 5, 6, 7, and 22 months in Malawi. Surveillance for post-neonatal mortality in children younger than 5 years was established throughout by a network of 26 000 local reporters who notified deaths in their community. The families were then visited at home by study staff to confirm details and complete a verbal autopsy. Surveillance for severe malaria and other conditions was strengthened in 18 sentinel hospitals serving part of the study area and maintained for 46 months. Uptake of RTS,S and other vaccines was monitored by the Expanded Programme on Immunisation in each country and independently through three household coverage surveys, at baseline, and at about 18 months and 30 months after introduction of RTS,S. The primary outcome of this impact evaluation was mortality due to any cause, except injury, in children eligible to receive three doses of RTS,S. Mortality rate ratios were estimated by comparing the ratio of deaths among vaccine-eligible age groups to deaths in non-eligible age groups between implementation and comparison areas. This evaluation is registered on ClinicalTrials.gov (NCT03806465) and is complete. FINDINGS: 158 clusters (66 in Ghana, 46 in Kenya, and 46 in Malawi) were selected and randomly assigned; 79 areas served as implementation areas and 79 as comparison areas. By the end of the 46-month evaluation period, 1 289 504 children had received the first dose of RTS,S, 1 158 850 had received the second dose, 1 068 039 had received a third dose, and 436 527 had received a fourth dose. Coverage assessed in 2022 was 82·8% (95% CI 80·7-84·9) for the first dose, 71·1% (68·8-73·5) for the third dose, and 39·9% (36·9-42·9) for the fourth dose. Excluding deaths due to injury, there were 5576 deaths in implementation areas versus 6152 in comparison areas in children eligible to have received the third dose of RTS,S, and 7534 versus 7044 deaths among non-eligible children. The mortality rate ratio was 0·87 (95% CI 0·77-0·97; p=0·016). INTERPRETATION: Introduction of the RTS,S malaria vaccine in routine immunisation programmes was associated with a significant reduction in mortality in young children, averting about one in eight deaths, in areas with moderate coverage of three doses of the vaccine and low uptake of the fourth dose. These results highlight the urgency to accelerate the deployment of malaria vaccines in areas of Africa where malaria continues to be a leading cause of child mortality. FUNDING: WHO; Gavi, the Vaccine Alliance; the Global Fund to Fight AIDS, Tuberculosis and Malaria; and Unitaid. TRANSLATIONS: For the French translation of the abstract see Supplementary Materials section.
13 May 2026
Read appraisal →Journal of medical systems
Feasibility, Adherence, Acceptance and Usability of a Multimodal Telemonitoring for Pediatric Post-COVID Syndrome: A Bicentric Pilot Study
Existing healthcare infrastructure struggles to meet the complex care required for pediatric Post-COVID Syndrome (pPCS). Telemonitoring offers potential to enhance care access, reduce patient burden, and ensure continuity. This study introduces and evaluates a novel, multimodal telemonitoring concept for pPCS with high translational potential for broader pediatric chronic and post-infectious conditions. Telemonitoring included a patient app, digital sensors (spirometer, smartwatch), Patient Reported Outcome Measures, chat/video consultations (VC), and a medical telemonitoring platform. Patients aged 12-17 years with diagnosed PCS were recruited from two pPCS outpatient university clinics in Bielefeld and Munich, Germany. Monitoring lasted three months. Evaluation focused on feasibility, adherence, acceptance, and usability, using monitoring data, the System Usability Scale (SUS), Technology Usage Inventory (TUI), and a custom survey completed by patients and parents. 30 patients (mean age: 15y ± 1.9; 57% female (17/30); mean Baseline Bell-Score: 36.4) and 30 parents participated. Adherence was high, with an average of 3.4 (smartwatch) to 4.6 (spirometry) measurements/week. Questionnaire response rate was 86% (411/480) and 97% (58/60) of VCs were conducted. SUS scores indicated very high usability (patients: 81.25/100; parents: 75.42/100). TUI results showed low skepticism, and high interest. Telemonitoring supported symptom management independent of in-person visits, despite sensor connectivity issues. This is the first study to demonstrate successful integration of telemonitoring in pPCS, with high adherence and positive feedback from all stakeholders supporting its potential. Despite occasional technical challenges and resource needs, this concept shows promise for broader hybrid telemonitoring care implementation in PCS and other post-infectious syndromes. TRIAL REGISTRATION: German Clinical Trials Register (DRKS), trial registration number: DRKS00029354. Registered 07 February 2023 - Retrospectively registered https://drks.de/search/en/trial/DRKS00029354/entails.
13 May 2026
Read appraisal →Vaccine
Factors influencing rabies vaccines immunogenicity during post-exposure prophylaxis: a systematic literature search and meta-analysis
BACKGROUND: Rabies post-exposure prophylaxis (PEP) requires timely appropriate wound management and vaccination (including concomitant rabies immunoglobulin [RIG], depending on vaccination history and wound severity) to ensure rapid increases in rabies virus neutralizing antibody (RVNA) titers, a surrogate marker of protection. In this systematic review and meta-analysis, we assessed factors influencing the immunogenicity of rabies vaccines administered as PEP. METHODS: PubMed, Embase, and The Cochrane Library were systematically searched for randomized controlled trials published in English, French, Spanish, or Portuguese from January 1, 1983 to March 28, 2022 reporting the immunogenicity of rabies vaccines, specifically rabies human diploid cell vaccine (Imovax Rabies), purified Vero cell rabies vaccine (Verorab), and purified chick embryo cell rabies vaccine (RabAvert/Rabipur), as part of PEP in healthy individuals. Pooled RVNA geometric mean titers (GMTs) and seroconversion rates at Day 14 (D14) post-vaccination, determined by rapid fluorescent focus inhibition test, were estimated using random effects meta-analyses. RESULTS: We identified 1040 studies, of which 67 (9689 participants across 140 intervention groups) were included. The pooled RVNA GMT across all vaccines at D14 post-vaccination was 8.19 (95% CI: 6.73-9.98) and did not differ significantly by vaccine, administration route, or RIG use; however, there were significant interlaboratory differences. Meta-regression analysis, including titration year, demonstrated a negative association with log-transformed RVNA GMTs, equating to a 4.18% reduction (95% CI: -5.89 to -2.44) in log-transformed GMTs per year during the period assessed. Across all vaccines assessed, the pooled seroconversion rate by D14 post-vaccination was 98% (95% CI: 97-98; n = 7023; I2 = 64%) and was not impacted by vaccine, administration route, RIG use, test laboratory, or titration year. CONCLUSIONS: Although RVNA GMTs appear to have decreased by titration year, there was no clinically meaningful impact on immunogenicity, and the three licensed rabies vaccines assessed are expected to provide similar protection.
13 May 2026
Read appraisal →PloS one
Maternal body mass index and the risk of early-onset Group B Streptococcus disease in newborns: A systematic review and meta-analysis
BACKGROUND: Early-onset group B Streptococcus disease (EOGBS) remains a leading cause of neonatal morbidity and mortality. The incidence can be substantially reduced by intrapartum antibiotic prophylaxis in women with defined risk factors. However, the role of high prepregnancy body mass index (BMI) as a risk factor remains unclear. This systematic review and meta-analysis therefore aimed to evaluate the association between maternal BMI and the risk of EOGBS, as well as related proxy outcomes, including intrapartum vaginal GBS colonization and rectovaginal or urinary GBS colonization before term. METHODS: We systematically searched MEDLINE, Embase, and Cochrane CENTRAL on the 28th of January 2026, for studies examining the relationship between pregestational BMI and EOGBS or its proxy outcomes. Eligible studies included observational and interventional designs but not case reports and conference abstracts. Risk of bias was assessed using the QUIPS tool. Random-effects meta-regression and sensitivity analyses were performed. RESULTS: We identified 19 eligible observational studies reporting data from a total of 3,707,047 women, encompassing 277,887 cases. For the risk of EOGBS and its proxy outcomes, assuming a log-linear association, our meta-regression showed a 2.4% increase in the odds ratio (OR) per unit increase in BMI. This corresponds to an OR of 1.4 (95% CI 1.1-1.6) for a BMI of 35 and 1.7 (95% CI 1.3-2.3) for a BMI of 45, compared to a normal BMI of 22.3. One very large study on 1,971,346 live singleton births with 780 EOGBS cases, found a hazard ratio of 2.4 (95% CI 1.7-3.4) for a BMI of 35.0-39.9 compared to normal BMI (18.5-24.9). CONCLUSIONS: Although the overall association appears modest, incorporating BMI may improve prevention strategies for EOGBS .
13 May 2026
Read appraisal →Vaccine
Effect of time-of-day vaccination on the antibody response to mRNA and protein COVID-19 vaccine in adults
Time-of-day vaccination has been suggested as a feasible method to boost COVID-19 vaccine immunogenicity particularly in high-risk groups. However, several studies report inconsistent findings. We explored if time-of-day vaccination influences antibody responses to a fourth dose of mRNA (Moderna bivalent vaccine; mRNA-1273.214/mRNA-1273.222) or protein (Novavax; NVX-CoV-2373) COVID-19 vaccine as part of a randomised controlled trial (RCT) in Melbourne, Australia. Furthermore, we assessed if time-of-day vaccination effects differed by vaccine type or sex. At day 28 post-vaccination, antibody responses to all SARS-CoV-2 variants tested were higher for morning compared to afternoon vaccination in the Moderna group. Males in the Moderna group responded with higher antibodies to all SARS-CoV-2 variants tested after morning vaccination while responses in females were unaffected by time-of-day vaccination. Time-of-day vaccination had no effect on the response to Novavax, regardless of sex. Larger randomised trials are needed to confirm these findings to optimise vaccine timing strategies.
13 May 2026
Read appraisal →Archives of women's mental health
Who is screened for perinatal mental health? findings from an academic health system in California.
PURPOSE: To identify sociodemographic characteristics, prenatal healthcare utilization, and health factors associated with completed mental health screenings during pregnancy and postpartum, respectively. METHODS: We examined electronic medical records (EMR) data on documented perinatal mental health screenings from over 6000 patients who delivered singleton infants within one academic healthcare system in California between 2021 and 2023. Dependent variables included having at least one Edinburgh Postnatal Depression Scale (EPDS) score documented in the EMR during (1) pregnancy and (2) postpartum, among those who completed postpartum care within 12 weeks of delivery. We used univariate frequencies to determine rates of completed screenings and logistic regression models to identify patient characteristics associated with completed screenings in each time period. RESULTS: Overall, 67% of patients completed screenings in pregnancy and 56% completed screenings in postpartum. In pregnancy, patients who were White, multiparous, did not prefer English, began prenatal care in the third trimester, and completed 10 or fewer prenatal care visits each had lower odds of completed screenings than their counterparts. In postpartum, patients who were White, privately insured, had vaginal deliveries, and had term births (at least 37 weeks of gestation) each had lower odds of completed screenings than their counterparts. CONCLUSIONS: Although California law requires perinatal mental health screening in pregnancy and postpartum , the identified inequities in screening suggest additional efforts are needed to ensure all perinatal patients are screened for mental health in accordance with the law. These efforts should be tailored to the populations least likely to be screened in order to achieve universal perinatal mental health screening.
13 May 2026
Read appraisal →Archives of women's mental health
Influences of adverse childhood experiences and weekly pregnancy stress on postpartum mental health symptoms: a machine learning examination
PURPOSE: The goal of this study was to understand how the timing, level, and fluctuation of pregnancy stress affected women's postpartum mental health while also considering their experiences of early life stress (adverse childhood events; ACEs). We hypothesized that overall stress level, as well as stress during particular pregnancy weeks, would influence postpartum mental health. We further hypothesized that fluctuations in weekly perceived stress levels across pregnancy would influence postpartum mental health among women who had experienced ≥ 4 ACEs. METHODS: We collected information on ACEs and weekly stress data from our participants during pregnancy (15 weeks until parturition). Women's depressive and anxiety symptoms were assessed at six-months postpartum. We employed a machine learning approach to explore the predictive utility of timing, level, and fluctuation of pregnancy stress on postpartum mental health symptoms. RESULTS: For all women, higher average stress level across all weeks of pregnancy predicted greater postpartum depressive and anxiety symptoms. Additionally, women with a history of ≥ 4 ACEs were susceptible to stress levels in weeks 20 of pregnancy (depressive symptoms only) and 26 (depressive and anxiety symptoms). Lastly, greater variability in stress levels across pregnancy was also associated with greater depressive symptoms for the women with ≥ 4 ACES. CONCLUSION: In addition to overall stress level, timing of pregnancy stress and fluctuations in stress levels across pregnancy are associated with postpartum mental health for women with a history of substantial ACEs, with implications for focused mental health interventions during pregnancy for these women.
13 May 2026
Read appraisal →European journal of nutrition
Association of daily diet and incidence of head and neck cancer: a prospective cohort study of UK biobank participants
PURPOSE: The association between daily diet and head and neck cancer (HNC) remains unclear. Therefore, this study aimed to systematically investigate the relationship between different types of diet and incident HNC. METHODS: This cohort study analyzed UK Biobank (UKB) data (2006-2021, n = 480,577) using Cox proportional hazards models to evaluate the associations between daily diet and incident HNC and its subtypes: laryngeal cancer (LC), oral cancer (OC), and oropharyngeal cancer (OPC). Subgroup analyses were further performed for sex, age, body mass index (BMI), and smoking status. RESULTS: This large prospective study identified significant dietary associations with head and neck cancer (HNC) risk during 11.8 years of follow-up. Protective associations emerged for moderate dried fruit consumption (Hazard Ratio (HR) = 0.77-0.81), daily milk intake (> 299 mL/day, HR = 0.71), and regular coffee drinking (HR = 0.77-0.84). Conversely, elevated risks were observed with frequent red meat (≥ 4 times/week, HR = 1.20), non-oily fish (≥ twice/week, HR = 1.45), refined grains (≥ 3 bowls or slices/week, HR = 1.14), and habitual salt addition (HR = 1.21). Subtype-specific patterns include the protective effects of whole grains and vegetables against laryngeal cancer and reduced oral cancer risk with limited poultry consumption. Notable variations were observed in sex (sex-specific milk/oily fish effects), age (differential fruit/vitamin impacts), and BMI (heightened red meat risk in normal-weight individuals). CONCLUSION: Our findings demonstrated significant associations between dietary patterns and HNC risk, identifying both protective and risk-enhancing food components. These results highlight the potential of dietary interventions in HNC prevention, with varying effects across cancer subtypes and demographic groups.
12 May 2026
Read appraisal →Vaccine
Effects of candidate vaccines against Zika virus infection: A systematic review of the clinical trials
INTRODUCTION: The 2015-2016 Zika virus (ZIKV) pandemic revealed a pathogenic potential, including Guillain-Barré syndrome and Congenital Zika Syndrome (CZS). Despite the decline in incidence, the potential for future circulation and the absence of specific antivirals underscore continued scientific interest in prophylactic vaccine development. OBJECTIVE: To synthesize evidence from clinical trials regarding the safety and preliminary immunogenicity of current ZIKV vaccine candidates. METHODS: This systematic review followed PRISMA guidelines (CRD420251056463). Searches were performed in MEDLINE, Embase, Web of Science, SciELO, and LILACS for clinical trials published between 2015 and 2025. Risk of bias was assessed using the Cochrane RoB 2 tool. RESULTS: Ten Phase 1 clinical trials were included, evaluating four platforms: inactivated virus (ZPIV, TAK-426, VLA1601), DNA (GLS-5700, VRC5283), mRNA (mRNA-1325, mRNA-1893), and viral vector (Ad26.ZIKV.001). All candidates demonstrated acceptable safety profiles, with predominantly mild-to-moderate and transient adverse events (e.g., injection site pain, fatigue, and headache); no vaccine-related serious adverse events were reported. Most platforms induced robust neutralizing antibody responses. Specifically, TAK-426 showed immune persistence for up to two years, while mRNA-1893 maintained responses for 13 months. The viral vector vaccine (Ad26.ZIKV.001) achieved 100% seroconversion with a single dose. Previous orthoflavivirus exposure did not significantly hinder vaccine-induced immunogenicity. Most studies presented a low risk of bias. CONCLUSIONS: ZIKV vaccine candidates across diverse technological platforms are safe and highly immunogenic. The evidence of long-term durability and the success of single-dose or mRNA regimens support the progression of the most promising candidates to Phase 2/3 trials.
12 May 2026
Read appraisal →Vaccine
Enhancing uptake of respiratory vaccinations in asthma and chronic obstructive pulmonary disease (COPD) patients: a systematic review.
INTRODUCTION: Despite influenza, pneumococcal and COVID vaccines being widely recommended for patients with chronic respiratory disease, vaccination rates in this cohort remain low. The aim of this systematic review is to identify interventions which are effective in increasing respiratory vaccination rates in adults with chronic obstructive pulmonary disease (COPD) or asthma. METHODS: The inclusion and exclusion criteria for the study can be found in the PROSPERO protocol (PROSPERO registration no: CRD42025588565). A search was run across four databases (MEDLINE, Embase, CENTRAL and ClinicalTrials.gov) in February 2025, which returned 2537 studies. Eleven studies were deemed to meet the study inclusion/exclusion criteria and these were narratively synthesised: four randomised clinical trials (RCTs), six longitudinal studies and one observational cohort study. Risk of bias was assessed using the Cochrane's Risk of Bias (RoB-V2) and ROBIN-I-V2 tools. Studies were categorised according to the COM-B model of behaviour change. RESULTS: All 11 studies consisted of COPD populations, with four studies also including asthma patients. Interventions focused on patient education, with/without involvement of a healthcare professional (HCP). Nine of the eleven studies showed a statistically significant improvement in influenza and/or pneumococcal vaccination rate with an intervention. No studies assessing COVID vaccine uptake in this population were suitable for inclusion. Most studies targeted patients' capability to get vaccinated through improving patients' and HCPs' knowledge. Fewer studies focused on social opportunity (e.g. support from other patients/HCPs) or automatic motivation (e.g. reminders). DISCUSSION: The published literature in this area is currently limited. Most studies are non-randomised and are at high-risk of bias, making meta-analysis not possible. Further research should assess the practicalities (physical opportunity) of vaccination, especially in low-income economies (where most respiratory patients reside) and standardising research methods to allow for future meta-analysis. OTHER: There is no funding for this review.
12 May 2026
Read appraisal →BMJ open respiratory research
Prevalence and determinants of drug-resistant pulmonary tuberculosis in the MENA region: a systematic review and meta-analysis
BACKGROUND: Multidrug-resistant tuberculosis (MDR-TB) is a constraining challenge for tuberculosis (TB) control worldwide. The Middle East and North African (MENA) region represents a significant part of the global MDR-TB burden. AIM: To estimate the pooled prevalence of MDR-TB and its determinants in the MENA region. METHODS: We searched for studies published in English and French on the subject up to 31 January 2026 on Web of Science, PubMed, Scopus and Cochrane, without time restriction. Original studies reporting data on the prevalence of MDR-TB in individuals living in the MENA region were selected. The meta-analysis was done using the random effects model considering the heterogeneity among the included studies and I 2 statistic was used to assess the heterogeneity. RESULTS: A total of 1239 articles were identified and 25 studies from 6 countries were included in this review. The prevalence of MDR-TB in the MENA region ranged from 0% (95% CI 0% to 4.1%) to 17.1% (95% CI 10.6% to 25.4%). The pooled prevalence was 3.54% (95% CI 2.18% to 5.72%) with a high heterogeneity, I2 =95.6%; 95% CI 94.4% to 96.5%. Previous exposition to TB treatment, HIV infection, smoking and the presence of comorbidities were the most reported associated factors. CONCLUSION: This review underscores the persistence of MDR-TB in the MENA region, suggesting insufficiency in TB control. Multisectoral interventions integrating strong prevention measures, standardised treatment protocols and measures to enhance treatment adherence should be implemented.
12 May 2026
Read appraisal →Journal of medical Internet research
Efficacy of Technology-Based Interventions on the Reduction of Loneliness: Systematic Review and Meta-Analysis
BACKGROUND: Loneliness is a widespread public health concern linked to increased risks of health problems. As populations age, the demand for effective interventions to mitigate loneliness continues to grow. OBJECTIVE: This meta-analysis aimed to examine the effectiveness of technology-based interventions in reducing loneliness. METHODS: A systematic literature search was conducted in Web of Science, PsycInfo, PubMed, Scopus, Google Scholar, Embase, and the Cochrane Library in August 2024. We included randomized controlled trials that examined the effectiveness of technology-based interventions compared with any control group in reducing loneliness across all age groups. Nonrandomized studies, qualitative research, and studies lacking sufficient statistical data for effect size calculation were excluded. After screening 1089 records, 7 studies involving 580 participants met the inclusion criteria. Data were extracted by 3 independent reviewers, with discrepancies resolved by a fourth reviewer. The risk of bias was assessed using the Cochrane risk-of-bias tool. A random-effects model was used to synthesize effect estimates, with standardized mean differences as the primary effect size metric. Heterogeneity was assessed using the Q statistic and I² index, and a prediction interval was calculated to estimate the expected range of true effects. RESULTS: We found a small and statistically nonsignificant overall effect of technology-based interventions on loneliness (pooled standardized mean difference=-0.21, 95% CI -0.59 to 0.17; 95% prediction interval -1.14 to 0.63). Substantial between-study variability was present (I²=57%; τ²=0.08; τ=0.28), and the prediction interval indicated that true effects in future studies may range from substantial reductions to moderate increases in loneliness. Differences between intervention types could not be examined due to the limited number of eligible studies. The Egger test showed significant funnel plot asymmetry (t5=-5.47; P=.003). However, since the trim-and-fill method identified no missing studies, the asymmetry is unlikely to be fully explained by publication bias. CONCLUSIONS: Unlike previous reviews, which focused primarily on older populations or included nonrandomized studies, this meta-analysis provides a rigorous synthesis of only randomized controlled trials across the lifespan. Our findings do not provide evidence for a reliable reduction in loneliness following technology-based interventions. Moderate heterogeneity indicates that effects differ across studies, and the limited number of eligible trials prevented the analysis of potential moderators. By incorporating robust prediction intervals and a broader age demographic, this study offers a more comprehensive view of the variability of intervention outcomes compared with existing literature. The wide prediction interval suggests that intervention effects may vary across settings. In practice, technology-based approaches should be viewed as supportive tools that require careful tailoring rather than universal solutions to loneliness.
12 May 2026
Read appraisal →Vaccine
Effect of neonatal BCG vaccination on oral herpes in early childhood: A nested study within a randomised controlled trial
BACKGROUND: Bacille Calmette-Guérin (BCG) vaccine, primarily used against tuberculosis, has off-target (non-specific) immunomodulatory effects, including potential protection against recurrences of latent herpes simplex virus (HSV) infections. Recurrent episodes of HSV herpes labialis (oral 'cold sores') affect a substantial proportion of the population, including young children, and there is currently no effective preventive intervention. METHODS: This pilot study, nested within the MIS BAIR randomised controlled trial (RCT), explored whether neonatal BCG vaccination, compared with no BCG vaccination, reduces the incidence and recurrence of herpes labialis during the first five years of life. FINDINGS: Among the 563 children (44% of 1272 randomised) who completed the 5-year follow-up, children in the BCG group were less likely to develop herpes labialis, compared with the control group (5% vs 8%; 38% relative risk reduction, p = 0.1). Risk of recurrence was significantly lower in the BCG group (33% vs. 71%; 53% relative risk reduction, p = 0.02). BCG-vaccinated children also reported a later onset of symptoms and a reduced impact on fluid intake during episodes. INTERPRETATION: This exploratory study suggests a protective role for neonatal BCG against HSV in children. However, its limitations, including its sample size, incomplete follow up and lack of virological confirmation, mean further studies are needed to confirm these findings. FUNDING: National Health and Medical Research Council (NHMRC) of Australia and others, as detailed in the acknowledgements.
12 May 2026
Read appraisal →International health
Neglected tropical diseases in conflict-related humanitarian emergency settings: a systematic review of the literature
Neglected tropical diseases (NTDs) are a group of 21 conditions affecting an estimated 1 billion people worldwide, causing significant mortality and morbidity. WHO has targeted their control, elimination or eradication by 2030, while highlighting that conflict and humanitarian emergencies are risks to achieving this. A systematic review of peer-reviewed literature was undertaken, using terms related to conflict-related humanitarian emergencies (CRHE), based on the Armed Conflict Location & Event Data Project codebook terms for defining emergencies and terms including all WHO-defined NTDs. After a two-stage screening process, 26 papers were included. Common challenges for NTD programmes in CRHE were healthcare access, infrastructure, population movement and data quality. Multisectoral collaboration between actors in conflict-settings was offered as a learning for NTD programmes, along with community participation and decentralisation. Evidence gaps were identified in the knowledge base for certain NTDs and in high-quality evidence for interventions in CRHE. Collaboration is a key area for focused improvement for NTD programmes in CRHE. This should be across sectors and extend to research and analysis approaches, to ensure the most effective interventions are identified and implemented and that NTD road map targets can be achieved.
12 May 2026
Read appraisal →BMJ mental health
Mental health in university students: an umbrella review grading the evidence for psychosocial interventions
QUESTION: Psychological distress is increasingly prevalent among university students, raising concerns about their mental health. This review aimed to assess the strength and credibility of evidence on the efficacy of psychosocial interventions for improving mental health in this population. STUDY SELECTION AND ANALYSIS: We conducted an umbrella review of systematic reviews (SRs) with meta-analyses of randomised controlled trials assessing psychosocial interventions among university students. Searches were performed in Medline, PubMed, Cochrane Central, PsycINFO, CINAHL, Epistemonikos and Campbell Collaboration from 1 January 2014 to 1 February 2026. Data on intervention type, comparator, outcome and study-level effect sizes were analysed using inverse-variance random-effects models with restricted maximum likelihood estimation of between-study heterogeneity (τ²). Strength of associations was evaluated according to umbrella review criteria, reporting quality using A MeaSurement Tool to Assess systematic Reviews 2 (AMSTAR-2) and certainty of evidence using Grading of Recommendations Assessment, Development and Evaluation (GRADE). FINDINGS: A total of 34 SRs were identified. After excluding overlapping syntheses, 28 unique meta-analyses from 12 SRs were included. Mindfulness-based interventions versus inactive controls for distress (standardised mean difference (SMD) -0.40; 95% CI -0.53 to -0.28) showed highly suggestive evidence (class II; GRADE: low; AMSTAR: high). Seven associations provided suggestive evidence (Class III): mindfulness-based interventions versus inactive controls for anxiety (SMD -0.54; 95% CI -0.81 to -0.27) and depression (SMD -0.52; 95% CI -0.65 to -0.39); cognitive-based interventions versus inactive controls for anxiety (SMD -0.48; 95% CI -0.62 to -0.34) and depression (SMD -0.60; 95% CI -0.75 to -0.45); cognitive-based interventions versus active controls for well-being (SMD -0.30; 95% CI -0.42 to -0.18); positive psychology interventions versus inactive controls for distress (SMD -0.22; 95% CI -0.35 to -0.10); and multimodal interventions versus inactive controls for distress (SMD -0.85; 95% CI -1.32 to -0.87). The remaining associations were weak or non-significant, generally supported by low or very low certainty and mostly low or very low reporting quality. CONCLUSIONS: The most robust evidence emerged for mindfulness and cognitive-based interventions, with some support also for positive psychology approaches. These interventions appear to improve depression, anxiety, distress and well-being among university students, though further rigorous research is needed. PROSPERO REGISTRATION NUMBER: CRD42023493618.
12 May 2026
Read appraisal →JMIR medical informatics
Machine Learning-Based Multidimensional Oximetry for Obstructive Sleep Apnea Screening: Development and External Validation
BACKGROUND: Obstructive sleep apnea (OSA) affects nearly one billion people globally and poses a substantial public health threat. Effective and accessible methods for OSA risk identification are urgently needed. OBJECTIVE: This study aims to develop and externally validate a machine learning model derived from multi-parameter pulse oximetry (SpO2) for OSA screening, and to evaluate its performance, interpretability, and robustness across sex and age subgroups. METHODS: Of 4156 screened participants, 2195 underwent polysomnography (internal cohort) and 446 received home sleep apnea testing (external cohort). Eight SpO2-derived parameters, including oxygen desaturation index (ODI), hypoxic burden (HB), and ST90 (percentage of sleep time with SpO2 < 90%), were used to construct models. Six machine learning algorithms were trained, with F1-score as the primary metric and area under the curve as the secondary metric. Model interpretability was assessed using Shapley additive explanations and intrinsic feature importance scores. RESULTS: Nonlinear parameter-risk relationships were observed between oximetry indices and OSA probability. The 4-parameter ODI-HB-MinSpO2-ST90 model achieved optimal performance (F1-score = 0.9516, area under the curve = 0.9879), surpassing all single-parameter models. Shapley additive explanations analysis identified ODI, HB, and MinSpO2 as key predictors. The ODI-HB-MinSpO2-MeanSpO2 configuration demonstrated superior performance in female and younger subgroups, whereas the ODI-HB-MinSpO2-ST90 model remained optimal for male and older participants. Categorical boosting outperformed other algorithms across multiple metrics and remained robust in both subgroup and external validation analyses. CONCLUSIONS: The multi-parameter oximetry model based on the categorical boosting algorithm provides a simple and accurate tool for OSA screening. Sex- and age-stratified strategies can further enhance its clinical applicability.
12 May 2026
Read appraisal →International health
Systematic narrative review on Menstrual health and hygiene (MHH) in Nigeria, Ghana, Liberia and The Gambia
Menstrual health and hygiene (MHH) are critical components of women's well-being, yet they continue to be overlooked in many low-resource settings. Addressing MHH issues in West Africa is crucial due to their widespread impact on education, health and gender equality, particularly among adolescent girls and women of reproductive age. This systematic narrative review consolidates the existing literature on MHH practices, knowledge, barriers and interventions in Nigeria, Ghana, Liberia and The Gambia. A comprehensive search was conducted across four databases (PubMed, Scopus, CINAHL Plus and Africa Journals Online) for studies published from 2000 to 2024. The search terms were related to menstruation, hygiene and the four West African countries. Both peer-reviewed articles and grey literature (Google Scholar, policy documents) were included to capture a broad spectrum of findings. Studies were selected based on their relevance to MHH in the target countries and data were extracted and analysed thematically. Of 345 articles identified, 26 studies met the inclusion criteria. Key findings highlighted the widespread lack of adequate MHM resources, such as sanitary products and functional sanitation facilities. Socio-economic disparities, cultural stigma and insufficient educational resources were major barriers to effective MHM. The review also found a strong link between inadequate MHM and adverse outcomes, including school absenteeism, psychological distress and increased vulnerability to infections. This review underscores the pressing need for comprehensive interventions to address MHH as a public health and human rights issue in Nigeria, Ghana, Liberia and The Gambia. Ensuring access to sanitary products, improved sanitation facilities and robust educational programs can help empower girls and women to manage menstruation with dignity, thereby improving their health, education and social participation.
12 May 2026
Read appraisal →Journal of epidemiology and community health
Children's views of obesity, body size and weight: systematic review of UK qualitative evidence
BACKGROUND: Understanding views about body size and weight is key to addressing both obesity and weight stigma. The views of younger children are not well understood and may differ in important ways from those of adults and young people. This review aimed to fill this gap. METHODS: Systematic review of qualitative evidence. We searched 19 database sources in February 2025 and included qualitative studies from the UK published since 2008 reporting data on children's (4-12 years) views of obesity, body size, body shape or weight. We assessed study quality using the Critical Appraisal Skills Programme checklist and conducted a thematic synthesis of the data. RESULTS: We included 34 studies. Study quality overall was fairly high. Children reported a range of perceived impacts of body weight, including health impacts, limitations on activities, bullying and teasing, which generated negative perceptions of overweight and fear of fatness. Ideas about body shape may be influenced by family members and by media or social media content. Children identified diet and physical activity as the main influences on body weight. There may be differences in views between girls and boys at older ages, although both are concerned about weight. We found very little data on differences relating to ethnicity or socioeconomic status. Children with overweight or obesity reported a pervasive experience of negative attitudes and bullying, which could be a barrier to participating in activities. CONCLUSION: Children, including very young children, generally hold very negative views of overweight and obesity. Overweight is seen to be linked with unhealthiness, limited agency and with being bullied. These links may influence how children understand messages about weight and health. PROSPERO REGISTRATION NUMBER: CRD42025650306.
12 May 2026
Read appraisal →Antiviral therapy
Factors associated with immunological non-response in HIV patients receiving antiretroviral therapy in Southeast Asia: A systematic review
ObjectiveThis systematic review summarizes factors associated with immunological non-response (INR) among people with HIV on antiretroviral therapy (ART) in Southeast Asia.MethodsWe conducted a systematic search of PubMed, ScienceDirect, DOAJ, and Lens.org for studies published between 2010 and 2025. Observational studies examining immunological outcomes following ART initiation and related factors were included. Study quality was assessed using the Newcastle-Ottawa Scale, and results were synthesized using a harvest plot.ResultTen eligible studies were included in the synthesis, comprising a total of 6,988 participants with substantial heterogeneity observed across studies. Factors associated with INR included age, sex, baseline CD4 cell count, HIV RNA levels, and co-infections. Among these factors, baseline CD4 cell count at the initiation of ART emerged as the most consistently associated determinant; lower baseline CD4 levels were linked to a higher risk of INR even with virological suppression.ConclusionThis review highlights baseline immunological status at ART initiation as a key predictor of immunological non-response in Southeast Asia. These findings underscore the critical importance of early HIV diagnosis and timely initiation of ART to prevent advanced immune damage and optimize immunological recovery.
12 May 2026
Read appraisal →Journal of speech, language, and hearing research : JSLHR
Vocal Biomarkers of Childhood Trauma: A Machine-Learning Approach to Speech Analysis
PURPOSE: Childhood trauma can disrupt communication, yet early signs often go unrecognized in regions affected by ongoing war, where immediate physical needs take precedence. Vocal biomarkers-acoustic features linked to emotional and motor regulation-offer a promising, noninvasive means of detecting trauma-linked speech disruptions. This study applied a hybrid framework to distinguish trauma exposure in Arabic-speaking children living amid active conflict. The aim was to support scalable, speech-based tools for early trauma identification in low-resource, humanitarian settings. METHOD: We analyzed 200 publicly available recordings of spontaneous speech from Arabic-speaking girls (ages 8-12 years): 100 trauma-exposed participants from Gaza (Palestinian) and 100 non-exposed controls from Jordan. Core acoustic features (fundamental frequency [F0], jitter, shimmer, harmonics-to-noise ratio [HNR], voice onset time [VOT], first formant, second formant) informed statistical testing and theory-driven composite indices. Exploratory features-including Mel-frequency cepstral coefficients and eGeMAPSv02 descriptors-were used to train binary classification models. Three classifiers (random forest, ridge regression, and logistic regression) were evaluated using nested cross-validation and bootstrap resampling. Composite indices were combined into a 0-10 Trauma Risk Score. Generalizability was assessed using an independent Lebanese cohort (n = 80), with the trained classifier applied using fixed exploratory features and preprocessing parameters. Core features were tested post hoc for cross-cohort stability. RESULTS: Trauma-exposed children showed reduced F0 and HNR, elevated shimmer and jitter, and prolonged VOT (Cohen's d > 1.2). Binary classification models achieved strong performance (area under the curve [AUC] = .89-.92); logistic regression reached AUC = .996 under cross-validation. Composite indices (AUCs > .90) stratified 68% into Moderate/High Trauma Risk. Lebanese validation confirmed generalizability, with theory-driven features showing stable predictive patterns. CONCLUSIONS: Vocal biomarkers reliably distinguished trauma exposure in Arabic-speaking children using a simple logistic regression model. This strong performance highlights the potential of speech-based tools as scalable, noninvasive methods for early trauma detection. Further validation is needed to support their use in diverse humanitarian and conflict-affected settings.
12 May 2026
Read appraisal →Journal of global health
Folate and global health review series, part 3: syntheses on cardiovascular, cerebrovascular, and metabolic diseases.
BACKGROUND: Cardiovascular and metabolic diseases account for an increasing share of morbidity and mortality globally. Folic acid supplementation has been linked to a lowered risk of stroke and some metabolic indicators due to its involvement in homocysteine and one-carbon metabolism and its role in the production of nitric oxide; however, the evidence on these associations is inconclusive. METHODS: We searched MEDLINE, Embase, CINAHL, the Cochrane Library, and the Database of Abstracts of Reviews of Effects from inception to February 2024 for systematic reviews and meta-analyses investigating the associations of folate (dietary intake, supplementation, or blood concentrations) with any cardiometabolic outcome. We performed screening, data abstraction, and risk of bias assessment in duplicate, and assessed the credibility of the evidence using predefined criteria. RESULTS: We identified 113 unique associations from 49 reviews. The included syntheses mostly had low risk of bias of and provided pooled risk estimates from intervention trials or prospective cohorts. A larger volume of evidence was available for composite cardiovascular outcomes, coronary heart disease, and stroke compared to other outcomes. No association reached a convincing or highly suggestive level of credibility. Six directional associations and five null associations met the criteria for a suggestive level of credibility. Three dose-response relationships, all at suggestive levels of credibility, supported an association between higher dietary folate intake and a reduced risk of coronary heart disease and stroke. CONCLUSION: The available evidence on the association between folate status and cardiometabolic outcomes primarily focuses on secondary prevention of cardiometabolic diseases and substantially underrepresents low- and middle-income countries. More large-scale studies are warranted to validate a relationship between folate status and cardiometabolic events or indicators. Overall, the evidence landscape around folate and cardiometabolic diseases appears to be limited both in volume and scope. REGISTRATION: PROSPERO: CRD42021265041.
12 May 2026
Read appraisal →International journal of biometeorology
Recent trajectories of biometeorology in the Global South: a systematic review of biometeorology research in the International Journal of Biometeorology
Literature reviews have become increasingly prominent in scientific discourse; however, few have critically examined the geographic distribution of research, particularly in the field of biometeorology, where studies remain disproportionately concentrated in the Global North. Building on previous regional reviews and special issues, this paper critically examines geographic disparities in publication trends, authorship, and methodological approaches to aid in identifying challenges and opportunities for equitable and justified future research. Using a PRISMA-style framework, 591 empirical studies conducted across 147 Global South countries were identified from a total of 3,046 publications in the International Journal of Biometeorology (IJBM) between 2000 and 2024. The review reveals a steady increase in contributions from the Global South over time, but highlights persistent gaps in representation, especially in author affiliation and research leadership. Thematic and methodological analyses highlight the diversity and innovation present in Global South contexts, while also revealing structural barriers to equitable participation in the field. This work advocates for more inclusive research practices and enhanced institutional support to bridge the divide between the Global North and South, fostering a more representative and collaborative future for biometeorology.
12 May 2026
Read appraisal →Journal of medical Internet research
Effectiveness of mHealth Interventions Aimed at Promoting Physical Activity and Reducing Sedentary Behavior on Work-Related Outcomes Among Workers: Systematic Review
BACKGROUND: Mobile health (mHealth) technologies have gained popularity and may play a key role in promoting health-related behaviors. However, the impact of mHealth interventions on work-related outcomes remains unclear. OBJECTIVE: We aimed to provide an overview of the effectiveness of mHealth interventions designed to encourage physical activity and decrease sedentary behavior on work-related outcomes. METHODS: A search was conducted in MEDLINE, Web of Science Core Collection, the Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews, and Ichushi-Web for all publications up to September 12, 2025, without language or date restrictions. We included studies which (1) investigated the impact of mHealth interventions promoting physical activity and reducing sedentary behavior on work-related outcomes such as absenteeism, presenteeism, work productivity, work performance, and workability; (2) were designed as a randomized controlled trial or nonrandomized study of interventions; (3) were conducted among workers; and (4) were published as full-text original articles in Japanese or English. Two researchers independently conducted the screening of titles and abstracts, followed by a full-text review to confirm study eligibility and extract the data. We assessed the risk of bias using the Cochrane Collaboration Risk of Bias tool for randomized trials (RoB 2) and the Risk Of Bias In Nonrandomized Studies of Interventions (ROBINS-I). Findings were narratively synthesized. RESULTS: In total, 4022 records were identified from databases and other sources. After removing duplicates, 3631 studies were screened, and 17 studies (12 randomized controlled trials and 5 nonrandomized studies of interventions) met the inclusion criteria. Of the 17 eligible studies with 18,805 participants, 12 showed a favorable effect direction on ≥1 work-related outcome, but the majority exhibited a high or critical risk of bias, raising concerns about the quality of the research. There was considerable heterogeneity across studies. CONCLUSIONS: Scientific evidence suggests that health promotion efforts that incorporate mHealth components to encourage physical activity and reduce sedentary behavior may have a favorable impact on work-related outcomes. However, the low methodological quality of the studies and their high heterogeneity due to the participant characteristics, intervention content, use of diverse work-related assessment tools, and different follow-up periods make it difficult to draw definitive conclusions about the effectiveness of the interventions. This review is the first to comprehensively synthesize evidence on the impact of mHealth interventions on work-related outcomes, extending prior reviews that primarily focused on traditional workplace-based interventions without mHealth components. This review also contributes to the field by offering guidance for future studies, including the potential value of megastudy designs that evaluate multiple interventions within the same population over the same period on the same outcomes. As a practical implication, these findings suggest that mHealth technologies may serve as a complementary strategy for supporting occupational health and productivity.
12 May 2026
Read appraisal →The New Zealand medical journal
The impact of cultural concordance between health professionals and patients: a narrative review
AIM: The aim of this article is to summarise international evidence on the impacts of cultural/ethnic concordance between patients and health professionals and to discuss the implications for New Zealand. METHOD: Database searches were conducted from August to September 2025 using Scopus, Embase and PubMed, using key terms related to health outcomes and cultural/ethnic concordance. RESULTS: A total of 25 relevant systematic reviews, meta-analyses and research studies were included for analysis. Overall, evidence is predominately from the United States of America and findings are variable. Cultural concordance is associated with improved communication quality, trust, satisfaction and perceived respect. Concordance is also associated with improved healthcare utilisation, medication adherence and uptake of preventative interventions. Some studies found concordance was associated with differences in clinical decision-making. Impact on clinical outcomes is mixed, with some studies finding concordance has a positive impact on caesarean section rates, diabetes management, surgical outcomes and addiction treatment, while others found no impact. CONCLUSION: Cultural concordance between patients and their health professionals matters, with evidence of impact on patient experience, communication quality, engagement and adherence, clinical decision-making and some clinical outcomes. Findings are inconsistent: the strength of association and groups which see the greatest benefit vary between studies. To reduce health inequities, we need to increase the diversity of the workforce and train all health professionals to provide non-racist, equitable care.
12 May 2026
Read appraisal →International health
Atopic dermatitis in Ethiopia: a systematic review and meta-analysis
Despite being a leading contributor to the global burden of skin disease there is no information on the national prevalence of atopic dermatitis in Ethiopia. Therefore, the purpose of this systematic review and meta-analysis was to estimate the pooled national prevalence of atopic dermatitis in Ethiopia. A computerized systematic search using multiple databases was performed in search of relevant English articles from the inception of the databases to 30 July 2023. It was done in accordance with the Preferred Reporting Items for Systematic review and Meta-Analysis (i.e. PRISMA) standard. R and R Studio software were used for statistical analysis. A random-effects model was used for calculating the pooled estimate of the prevalence of atopic dermatitis. Forest plots and tables were used to represent the data. We found 10 full-text observational studies with 25 920 participants suitable for the review after checking for inclusion and exclusion criteria. The overall pooled prevalence of atopic dermatitis in Ethiopia was 12.75% (95% CI 8.32 to 17.17%). The subgroup analysis found that the atopic dermatitis pooled prevalence was 7% (95% CI 3 to 10%), 17% (95% CI 4 to 30%) and 20% (95% CI 15 to 24%) in the Oromia region, Amhara region and Addis Ababa city administration, respectively. This study demonstrates that atopic dermatitis is highly prevalent in Ethiopia, affecting approximately one in eight individuals, with significant geographical variations. To effectively address this condition, it is crucial to implement awareness campaigns, prioritize specialized training for healthcare professionals, allocate resources to high-prevalence areas, establish a national registry for monitoring, develop community support programs and encourage further research, as there are currently few studies on the condition.
11 May 2026
Read appraisal →International health
Pneumonia in Ghana: prevalence, mortality and antimicrobial resistance-a systematic review and meta-analysis
Pneumonia is a major cause of morbidity and mortality in Ghana, especially among children <5 y of age and the elderly. However, comprehensive data on its prevalence and distribution remain limited. This systematic review addresses this gap by analysing the prevalence, regional variations, risk factors, antimicrobial resistance and mortality rates of pneumonia in Ghana. We searched PubMed, ScienceDirect, Web of Science and African Journals Online databases, including 21 studies with a total of 124 582 participants. A random-effects meta-analysis estimated pooled prevalence and subgroup differences based on age, region and participant type. Heterogeneity was assessed using the I2 test and meta-regression, with sensitivity analysis also conducted. Study quality was evaluated using standardized Joana Briggs Institute checklists for prevalence studies. The pooled prevalence of pneumonia in Ghana was 22.01%, with significant regional variations. The highest prevalence was observed in a study conducted in the Greater Accra and Northern regions (32.31%), while the lowest was in the Upper West (4.83%). The prevalence in children <5 y of age was 17.79%. Hospitalized patients had a higher prevalence (22.14%) than community children (21.49%). Streptococcus pneumoniae was the most common pathogen, with high resistance (>70%) to co-trimoxazole, gentamicin and tetracycline. Key risk factors included indoor air pollution and seasonal changes. The mortality rate for pneumonia was found to be 3.07%. This systematic review highlighted significant regional disparities, pathogen resistance patterns and environmental risk factors that shape the burden of pneumonia in Ghana, providing critical evidence for targeted public health strategies. The findings highlight avenues for future research, including environmental drivers of transmission, focusing on underreported regions and surveillance of antibiotic resistance of pathogens isolated from pneumonia patients.
11 May 2026
Read appraisal →JMIR formative research
Feasibility of Integrating Wearable Devices and Ecological Momentary Assessment for Real-Time Environmental Exposure Estimation: Proof-of-Concept Study
BACKGROUND: Environmental exposures such as heat and air pollution are critical determinants of health, yet traditional assessment methods rely on stationary monitors or residential address proxies that fail to capture the exposures that individuals experience throughout the day. OBJECTIVE: This pilot study aimed to assess the feasibility of integrating ecological momentary assessment (EMA), wearable devices, and continuous GPS tracking to capture real-time environmental exposures and to explore associations with concurrent health outcomes. METHODS: In total, 7 young adults (aged approximately 16 to 24 years; 5/7, 71% female) wore Fitbit Charge 6 watches from July 2025 to August 2025 (mean 28.1, SD 1.1 days), recording sleep quality and duration, resting heart rate, breathing rate, heart rate variability, and physical activity. GPS location measured at up to 5-minute intervals (mean 19.7, SD 25.8 measurements per day) was linked to ambient temperature, humidity, and air pollution data (particulate matter <2.5 um or <10 um in diameter, nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide) derived from monitoring stations, satellites, and climate models using data-integration algorithms accessed via an application programming interface. EMA surveys administered 3 times per day captured participants' emotional states and location (inside or outside). Feasibility targets were ≥3 GPS measurements per day, ≥1 survey completed per day, and complete sleep data on ≥50% of days. We examined exploratory bivariate correlations between environmental exposures, physiological measures, and self-reported mood, adjusting for multiple comparisons using false discovery rate correction. RESULTS: Of the 7 participants, 5 (71%) met predefined feasibility targets. Mean compliance included 565 (SD 457) GPS coordinates per participant, 1.4 (SD 0.2) EMA surveys per day, and complete Fitbit sleep data on 64% (SD 27%) of days. Surveys identified barriers to compliance, including perceived complexity of the system and forgetting to put the Fitbit watch back on after removing it. Exploratory correlations (6/7, 86% of participants with complete Fitbit data) revealed associations between nitrogen dioxide and heat exposure and reduced heart rate variability (a marker of parasympathetic tone), and between air pollutants (sulfur dioxide) and increased negative emotions. Heat exposure showed a paradoxical pattern of lower self-reported sadness but reduced heart rate variability with higher levels of heat exposure. Given the small sample size, these correlations should be considered preliminary and hypothesis generating rather than definitive findings. CONCLUSIONS: This study demonstrates that the multimodal integration of wearable devices, GPS tracking, and EMA is feasible for capturing real-time environmental exposures and concurrent health outcomes in young adults. This approach addresses critical exposure misclassification issues in environmental health research that relies on residential addresses as proxies. Preliminary patterns suggest complex relationships between environmental exposures and both physiological and emotional outcomes, warranting further investigation in larger, more diverse samples. This approach could inform future personalized environmental health interventions.
11 May 2026
Read appraisal →PloS one
Research on interpretable machine learning modeling and spatial prediction of cross-landform landslide disaster mechanism: A case study of Shaanxi Province
The differential understanding of the landslidetriggering mechanisms across various geomorphic units is vital for enhancing regional disaster prevention. This study investigates the Loess Plateau area in northern Shaanxi and the Qinba Mountain Area in southern Shaanxi as the study areas, and constructs a 15dimensional evaluation factor system covering topography, geology, vegetation, and human activities. After eliminating collinearity factors via double tests of the Pearson correlation coefficient and variance inflation factor, Bayesian optimization is used to optimize hyperparameters for CatBoost, Random Forest, LightGBM, and XGBoost, and the SHAP framework is combined to perform global attribution, single-factor dependency analysis, and interaction-effect quantification. The results demonstrate that CatBoost performs best across both geomorphic areas, achieving AUCs of 0.8307 and 0.8252 in the test sets. In northern Shaanxi, a discrete patch pattern driven by "human-water" coupling is observed, with population density and the topographic moisture index contributing 37.2%. In contrast, Southern Shaanxi exhibits a continuous, band-shaped distribution controlled by "structure-topography" is observed, and elevation and lithology dominate the model's decision-making. The SHAP-dependent map identified cross-geomorphic differences in the population density threshold of 99.83 people/km2, the slope threshold of 2.21° in northern Shaanxi, and the elevation threshold of 1194.73m in southern Shaanxi. Furthermore, the interaction network revealed an antagonistic effect of DEM and POP in northern Shaanxi and of DEM and LULC in southern Shaanxi. The framework proposed a quantitative, explainable basis for differentiated disaster prevention strategies in this research.
11 May 2026
Read appraisal →International health
Global trends in travel-related antimicrobial resistance: a systematic review, 2020-2024
Antimicrobial resistance (AMR) is a growing global health threat, with international travel playing a key role in the spread of resistant bacteria. This systematic review examines trends in travel-associated AMR from 2020 to 2024. A search of PubMed, Scopus and Web of Science identified 10 studies involving 359 AMR isolates. Using the Newcastle-Ottawa scale, the study quality was assessed and findings were synthesised to identify patterns in prevalence, diversity and geographic spread. Results revealed a consistent rise in travel-associated AMR, particularly from regions such as Southeast Asia and Africa, which acted as major sources of diverse resistant pathogens. These include extended spectrum beta-lactamase-producing Escherichia coli, multidrug-resistant (MDR) Corynebacterium diphtheriae and colistin-resistant Enterobacterales. The number of MDR strains increased over time, making up 15.3% of cases by 2024. Healthcare exposure during travel emerged as a significant risk factor. Overall, the prevalence and diversity of AMR bacteria linked to travel have risen steadily, highlighting the urgent need for global cooperation. Enhanced surveillance, antimicrobial stewardship, infection control measures and international collaboration are essential to curb the spread of these dangerous pathogens.
11 May 2026
Read appraisal →American journal of epidemiology
Predicting first onset of suicide attempt among children with suicidal ideation or non-suicidal self-injury using machine learning: a prospective population-based cohort study
While children with suicidal ideation or non-suicidal self-injury (NSSI) are at high risk of suicide, most do not attempt suicide. This study aims to identify predictors of first suicide attempts among children with suicidal thoughts or NSSI. We utilized longitudinal data from the Adolescent Brain and Cognitive Development study to examine a broad range of risk factors in children reporting suicidal ideation (N = 344, mean age = 9.93) or NSSI (N = 261, mean age = 9.88) at baseline, predicting first attempt of suicide during a 4-year follow-up. Predictive models were developed through bivariate feature selection followed by Discrete-Time Random Survival Forest machine learning, identifying predictors of subsequent suicide attempts. During the follow-up, 40 of 344 children (11.6%) with suicidal ideation, and 32 of 261 children (12.3%) with NSSI at baseline initiated suicide attempts. For suicidal ideation, risk for attempting suicide increased with caregiver-reported NSSI, witnessing domestic violence, severity of suicidal thoughts, being female, online social screen use, and less parental supervision. For NSSI, risk of suicide attempt increased with witnessing domestic violence, anxiety disorders, caregiver-reported NSSI, being female, and disruptive, impulse control, and conduct disorders. Our findings shed light on the development of population-based suicide prevention strategies for children.
11 May 2026
Read appraisal →Tobacco control
Vaping cessation interventions: a systematic review and meta-analysis
OBJECTIVE: Electronic nicotine delivery systems (ENDS), such as e-cigarettes, have surged in popularity. While long-term risks remain unclear, known dangers include nicotine addiction, E-cigarette or Vaping Use-Associated Lung Injury and potential extrapulmonary effects on the heart, immune system and neurodevelopment. Addressing ENDS addiction may require strategies akin to smoking cessation. However, evidence is lacking; there are no currently approved vaping-cessation aids. The objective of this review is to summarise the available literature addressing interventions for vaping cessation. DATA SOURCES AND STUDY SELECTION: A librarian-assisted search was conducted in MEDLINE, Embase and Scopus, as well as preprints in Europe PMC, Open Science Framework, and the grey literature searches until January 2024. Six included studies used self-report methods to determine the abstinence rate, while one study used cotinine-level-verified self-reported abstinence. We included randomised controlled trials (RCTs) that examine 'rates of vaping cessation' outcomes. An intention-to-treat approach was used for data extraction, and random-effects meta-analyses models were applied. DATA SYNTHESIS: Seven RCTs were included, which studied pharmacological therapy, digital interventions and/or educational content. The primary meta-analyses demonstrated a statistically significant increase in the odds of achieving 7-day point prevalence abstinence (PPA) (OR 1.52, 95% CI 1.15 to 2.01, number of participants=3244, moderate-certainty) and continuous abstinence (OR 2.71, 95% CI 1.31 to 5.61, number of participants=164, low-certainty) following intervention. A non-significant increase in odds was noted at 30-day PPA (OR 1.32, 95% CI 0.72 to 2.42, number of participants=1994, very low certainty). CONCLUSIONS: Vaping cessation interventions increase 7-day PPA rates at 1-12 months follow-up and this was consistent across prespecified subgroup analyses of the intervention type, outcome and duration of follow-up. More high-quality studies with reproducible findings are needed to enhance the certainty of the evidence and guide clinical interventions. PROSPERO REGISTRATION NUMBER: CRD42022383670.
11 May 2026
Read appraisal →International journal of health care quality assurance
Understanding trust in mandatory telemedicine use during COVID-19: a modified health belief model approach
PURPOSE: This study explores the determinants of trust in telemedicine when its use was mandated during the COVID-19 pandemic in South Korea. It extends the health belief model by incorporating two service related constructs: service quality and perceived cost. DESIGN/METHODOLOGY/APPROACH: An online survey was conducted with 288 individuals who were confirmed COVID-19 patients and required to use telemedicine services during isolation. Partial least squares structural equation modeling was applied to examine the relationships between health beliefs including perceived severity, perceived susceptibility and self-efficacy, service perceptions such as service quality and perceived cost, trust in telemedicine and behavioral intention to use telemedicine services. FINDINGS: The results showed that self-efficacy, service quality and perceived cost positively influenced trust in telemedicine. In contrast, perceived severity and perceived susceptibility did not have a meaningful impact. Trust was found to be a key factor in shaping patients' intention to continue using telemedicine services. Overall, the proposed model was supported, highlighting the importance of confidence and service related perceptions in building trust under mandatory usage conditions. ORIGINALITY/VALUE: This study provides empirical evidence on trust formation under mandatory telemedicine use, a scenario rarely explored in the literature. It demonstrates that trust is primarily driven by users' self-efficacy and service perceptions rather than by health risk perceptions, offering practical guidance for enhancing remote care engagement during policy enforced use conditions.
11 May 2026
Read appraisal →PloS one
Data fusion-based traffic prediction and software decision support for recreational suburban roads
Predicting traffic flow on mountainous suburban roads is challenging due to highly variable environmental, temporal, and traffic-related conditions. This study focuses on Kandovan Road, a critical route with complex behavioral patterns influenced by weather conditions, calendar events, and road-specific characteristics. To improve forecasting accuracy, eight machine learning and deep learning models were implemented, including Deep LSTM, Random Forest Regressor, XGBRegressor, Transformer, ST-ResNet, Conv-LSTM, Bidirectional LSTM, and LSTM-GAN. The models were trained and evaluated using traffic, weather, and event datasets from 2017 to 2023, with performance measured through MAE, RMSE, MSE, and MAPE metrics. Among the evaluated models, the Random Forest Regressor achieved the highest accuracy with an R² score of 0.88 and a low average error. This result demonstrates its strong ability to model non-linear and dynamic traffic patterns. The results indicate that integrating diverse data sources significantly enhances traffic prediction performance on mountain roads. Additionally, a dedicated traffic forecasting software system was developed to visualize real-time predictions and provide an operational decision-support tool for traffic authorities. The outcomes of this work support more efficient traffic management, improved road safety, and sustainable transportation planning in challenging terrains.
11 May 2026
Read appraisal →BMJ global health
Transforming reproductive healthcare delivery through telemedicine services expansion: evidence from a mixed-methods pilot evaluation in rural Ghana
BACKGROUND: In 2021, Ghana's National Comprehensive Abortion Care Standards and Protocols recognised telemedicine as an approved delivery model for early medical abortion (EMA). Following a successful pilot in Accra, MSI Reproductive Choices Ghana expanded their telemedicine model to more rural areas and broadened their package of sexual and reproductive health (SRH) services to include fertility evaluation. This study evaluates the expanded model. METHODS: A mixed-methods evaluation (January 2024 to March 2025) drew on routine clinical data, courier and call centre tracking, client feedback surveys, and qualitative, individual in-depth interviews with telemedicine clients to assess clinical safety, service utilisation and user experience. Quantitative analysis included descriptive statistics and unadjusted logistic and ordinal regression. Qualitative interviews with clients explored feasibility, acceptability and implementation challenges. A deductive, thematic analysis was conducted with the support of Delve qualitative research software and guided by the Consolidated Framework for Implementation Research. RESULTS: A total of 2721 clients accessed telemedicine services, with 70.0% receiving EMA and 29.5% short-term contraceptive methods. Among EMA clients reached for follow-up, 96.9% reported complete abortion with no further intervention. Satisfaction was high: 89.4% would recommend the service, and 78.2% would use it again. Qualitative findings highlighted that clients valued privacy, convenience and autonomy, particularly in stigmatised or crowded spaces. Barriers to accessing services included unclear eligibility criteria, limited digital access and misperceptions that the service was for abortion only. Most clients contacted the service between 4 and 6 weeks' gestation. Post-abortion contraception uptake was 24.8%, with no significant variation by age or location. Nearly half of clients reported having no other way to access care. CONCLUSIONS: Telemedicine is a feasible, safe and acceptable model for SRH delivery in Ghana. Findings will inform national scale-up and strategies to strengthen equity, communication and service integration.
11 May 2026
Read appraisal →CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne
Screening for high-risk drinking and alcohol use disorder: update of the 2023 national clinical practice guideline
BACKGROUND: Current screening tools for harmful alcohol consumption have fallen out of step with recent guidance on the health risks of alcohol. To address this gap, the Canadian Research Initiative in Substance Matters updated the screening recommendations for high-risk drinking and alcohol use disorder (AUD) in the 2023 national clinical practice guideline. METHODS: Following a systematic review of literature published between Jan. 1, 2013, and Feb. 24, 2023, that examined screening tools for high-risk drinking and AUD, the updated recommendations were developed by a multidisciplinary national committee, which included people with lived and living experience. We scored the recommendations and certainty of evidence using the Grading of Recommendations, Assessment, Development, and Evaluation tool. We used the Appraisal of Guidelines for Research and Evaluation II instrument and the Guidelines International Network's principles for disclosure of interests and management of conflicts to ensure the update met international standards for transparency, high quality, and methodological rigour. RECOMMENDATIONS: Acknowledging that time constraints are the most commonly reported barrier to universal alcohol screening, we developed 5 recommendations involving a simple screening method, to identify and address both unhealthy alcohol consumption and more serious problems related to alcohol. The recommendations include asking all patients about alcohol consumption and providing educational support to all those who drink above Canada's Guidance on Alcohol and Health's low-risk threshold. We propose a simple screening algorithm to optimize and tailor further intervention, including when to assess for possible AUD. INTERPRETATION: The revised screening recommendations represent a timesaving and pragmatic approach intended to be a resource for universal screening for alcohol risks and problems. The recommendations streamline the process of identifying and addressing the health needs of those who consume alcohol in a hazardous way or may have more serious problems related to alcohol.
11 May 2026
Read appraisal →BMJ open
Potential harms of social prescribing: a global umbrella review and dark logic model
OBJECTIVES: Social prescribing has provided a lifeline to people, capturing the importance of quality support offered via community connections. It has not been exempt from difficulties, resulting in low-quality evidence on effectiveness in part due to high drop-out rates and lack of controls. While these have been the focus of recent research, less attention has been paid to the safety implications of social prescribing. This review aims to understand safety implications of social prescribing interventions and to build a dark logic model of how harms are produced. DESIGN: Using review of review (umbrella) methodology, we searched nine databases to June 2024. DATA SOURCES: Medline/Ovid, Embase, PsycINFO, Cochrane Library/Wiley, Web of Science and Scopus) were searched from 1 January 2010 to 3 June 2024. ELIGIBILITY CRITERIA: Included reviews were systematic/scoping/narrative reviews or meta-analyses, which synthesised primary data collected from any person in receipt, involved in delivery or the commissioning of social prescribing interventions. The context of the review was social prescribing interventions/services based in primary healthcare (statutory) or third sector (non-statutory) in any country. Only reviews that were published in English and in peer-reviewed journals were included. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers extracted data from included reviews using the Typology of Harms Framework (which includes five categories of harms associated with interventions: physical, psychological, group/social, equity and opportunity harms) and to build a dark logic model to understand what contributes to these harms. RESULTS: Sixteen reviews were included, reporting on social prescribing research including a link worker. Of the identified harms, we found that opportunity harms (harm related to the cost, inappropriate or ineffective interventions) were most reported. There was also evidence extracted to suggest plausible psychological, equity (impact caused by inequity in provision, delivery or access) and group/social harms (impact that overly or inadvertently excludes a person). No physical harms were identified. CONCLUSIONS: Social prescribing, as with any delivery of care, has the potential to cause harm. We identified a range of potential harms (psychological, group/social, equity or opportunity harm) from social prescribing; however, it is unlikely to be an exhaustive list. We provide two clear outcomes: (1) the need for robust design of social prescribing research, including collection of data on the incidence and prevalence of harms, (2) recognition of the potential for harm from social prescribing and to address these where practicable.
11 May 2026
Read appraisal →Journal of medical Internet research
Characterizing Physical Activity Trajectories Preceding Incident Major Depressive Disorder Diagnosis With Consumer Wearable Devices in the All of Us Research Program: Retrospective Nested Case-Control Study
BACKGROUND: Low physical activity (PA) is a well-established risk factor for major depressive disorder (MDD). However, the temporal dynamics of PA preceding an incident clinical diagnosis of MDD remain poorly characterized, particularly using long-term, objective measures collected in real-world settings. OBJECTIVE: This study aimed to characterize trajectories of wearable-measured PA during the year preceding incident MDD diagnosis and identify the timing of within-person changes. METHODS: We conducted a retrospective nested case-control study using linked electronic health record and wearable (Fitbit) data from the All of Us Research Program. Adults with at least 6 months of valid Fitbit PA data in the 12 months preceding diagnosis were included. Incident MDD cases were identified based on a first electronic health record-recorded diagnosis and matched to MDD-free controls on age, sex, BMI, and calendar time of diagnosis, with up to 4 controls per case. Daily steps and moderate to vigorous PA (MVPA) were aggregated into monthly averages. Linear mixed-effects models were used to compare prediagnostic PA trajectories between cases and controls over a retrospective time scale from -12 to 0 months. Among cases, within-person contrasts were used to identify when PA levels first showed statistically significant deviations relative to levels observed 12 months before diagnosis. Exploratory analyses assessed heterogeneity by demographic factors. RESULTS: The analytic cohort included 4104 participants (n=829, 20.2% incident MDD cases and n=3275, 79.8% matched controls; n=3355, 81.7% women; median age 48.4, IQR 36.3-61.3 years). Compared with controls, individuals who developed MDD exhibited consistently lower overall PA and significant downward trajectories in both daily steps and MVPA during the year preceding diagnosis (global trajectory tests; P<.001 for both outcomes). Differences widened progressively over time, indicating accelerating declines as diagnosis approached. Among cases, statistically significant changes in daily step counts emerged approximately 4 months before diagnosis (-145, 95% CI -253 to -37 steps vs month -12; P=.02) and reached -428 (95% CI -531 to -326) steps at diagnosis (P<.001). Declines in MVPA emerged approximately 5 months before diagnosis (-2.48, 95% CI -4.32 to -0.64 minutes; P=.02) and reached -5.61 (95% CI -7.35 to -3.86) minutes at diagnosis (P<.001). Furthermore, exploratory analyses suggested heterogeneity in prediagnostic trajectories across demographic subgroups, including steeper declines among men, more pronounced reductions in activity intensity at older ages, and persistently lower activity levels with flatter trajectories among individuals with obesity. CONCLUSIONS: Unlike prior studies lacking objective PA assessment before MDD diagnosis, this study linked wearable and clinical data to characterize long-term prediagnostic trajectories in real-world settings. We observed sustained within-person declines emerging 4 to 5 months before diagnosis, providing insights into temporal dynamics preceding clinical recognition. These findings suggest that wearable-based monitoring may offer scalable early signals for risk stratification, prevention, and intervention for MDD.
11 May 2026
Read appraisal →JMIR formative research
The Role of Trust in Text Messaging for Promoting Patient Portal Activation Among Low-Income Patients: Quality Improvement Project
BACKGROUND: The increasing reliance on patient portals for electronic health records has widened the digital health care access gap, particularly among low-income and Medicaid-insured populations. However, resources exist to assist low-income patients with portal enrollment; in obtaining a free smartphone; and, in New York, in obtaining low-cost internet. Automated bidirectional SMS text messaging offers a scalable and cost-effective strategy for identifying low-income patients' digital health needs and eligibility for resources by using screening questions and providing tailored information on how to access available resources. OBJECTIVE: This study aimed to increase portal access among low-income patients using automated bidirectional SMS text messaging and assess its feasibility and acceptability. METHODS: This quality improvement initiative involved sending automated, bidirectional SMS text messages in English to 12,381 Medicaid-insured and/or low-income patients from a primary care practice. Messages assessed patients' digital health needs and provided adaptive, personalized resources and assistance for enrolling in the patient portal and for accessing digital technology. We assessed response rates and follow-up portal enrollment rates. We surveyed participants regarding the acceptability, appropriateness, and usability of the SMS text messaging intervention, as well as their subsequent use of the patient portal. We performed descriptive statistics and a binomial probability test. RESULTS: In total, 9.2% (1140/12,381) of patients responded to the SMS text messages, with 3.9% (481/12,381) opting out and 5.3% (659/12,381) actively engaging. Among respondents, 71.1% (469/659) completed the follow-up survey. Respondents were predominantly female (336/469, 71.6%), with ages ranging from 18 to 65 years or older. Most respondents rated the message's clarity (420/469, 89.6%), its usefulness (400/469, 85.2%), and the demonstration of care by their health team (350/469, 74.6%) favorably. Concerns regarding privacy (61/469, 13%) and trustworthiness (71/469, 15%) were noted. Notably, 71% of initially unenrolled patients activated their patient portals after the intervention (P=.007), exceeding the hypothesized expectations. CONCLUSIONS: Automated bidirectional SMS text messaging had mixed effects on promoting patient portal use among low-income patients. Response rates to SMS text messages were low when delivered from an unknown phone number. Among responders, most reported that these messages were useful and that they would recommend them to others. Research is needed to determine optimal strategies for introducing the program and vendor phone numbers to patients to improve engagement.
11 May 2026
Read appraisal →Transactions of the Royal Society of Tropical Medicine and Hygiene
Quality of life in Indian people affected by leprosy? A systematic review from the country with the highest burden of leprosy cases.
Quality of life (QoL) is important for people with leprosy since the disease can cause physical and psychological problems. These problems may result in stigma and social discrimination. India reported 107 851 new leprosy cases for the year 2023-24, accounting for 61.6% of new cases detected globally. This systematic review was conducted to assess the QoL among people affected by leprosy in India using existing literature. The Scopus, PubMed and Infolep databases were searched for articles for this systematic review and included only studies conducted in India. The critical appraisal tool of cross-sectional studies (AXIS) was used to assess the study quality and risk of bias. The search identified 253 articles. After screening titles and abstracts, 23 full-text articles were assessed for eligibility and 12 studies were included in the systematic review. The World Health Organization Quality of Life-Bref instrument was used to measure QoL. Of the 12 studies, the factors of disability (9 studies) and old age (8 studies) were highly associated with low levels of QoL. Five studies identified that low levels of QoL are associated with being female with the leprosy. Early identification and prevention of disabilities are important steps in improving the QoL. Increased investment is needed in leprosy programmatic activities and research to achieve the target of zero leprosy.
10 May 2026
Read appraisal →JMIR human factors
Identifying Skill and Usability Barriers to Digital Health Tool Use Among Older Adult Patients in US Safety Net Clinics: Mixed Methods Study
BACKGROUND: Despite their benefits, digital health tools often face adoption barriers because of the digital divide. Identifying the fundamental user skills required to effectively navigate these tools and the usability barriers is essential to addressing disparities in use. OBJECTIVE: This study aimed to identify the skill and usability barriers to using digital health tools. METHODS: This study included English-, Spanish-, or Cantonese-speaking patients, aged ≥50 years, who received care at an urban safety net health system in the United States. Participants completed a survey examining sociodemographic characteristics and digital health tool use and were observed and video recorded as they navigated four digital health care tasks: (1) launch a video visit, (2) visit a health website through a URL, (3) log in to the patient portal, and (4) sign up for a patient portal account. Participants who could not independently perform the tasks received additional support. Tasks were conducted in English, while instructions and additional assistance were provided in each participant's preferred language. Video recordings were thematically coded to identify the fundamental skills needed for effective digital tool use and usability barriers in the design of digital tools. We examined whether task independence was associated with participant demographics and thematic categories using Kruskal-Wallis, χ2, and Fisher exact tests. RESULTS: In total, 74% (34/46), 52% (31/60), 71% (44/62), and 70% (43/61) of participants (N=64) independently completed digital tasks 1, 2, 3, and 4, respectively. Older age, minoritized races and ethnicities, non-English language preference, lower educational attainment, access to cellular data only or no internet access, and lack of a portal account were associated with a higher likelihood of requiring assistance or being unsuccessful at completing each task (P<.001, except for older age [P=.004]). The qualitative coding of video recordings identified 3, 4, and 6 categories of typing, navigation, and human-computer interaction (HCI) skills, respectively, as fundamental skills required to independently complete digital tasks. χ2 and Fisher exact tests indicated significant associations between most typing, navigation, and HCI categories and independent task completion. We coded usability barriers as one of 6 learnability challenges or 3 operability challenges. CONCLUSIONS: This study identified that independent use of digital health tools requires fundamental typing, navigation, or HCI skills as well as high usability of digital tools. The inclusion of 4 different digital tasks added specificity to the type of skills and usability considerations necessary to ensure accessibility of digital health tools to diverse older adults. This study underscores the need for vendors to cocreate digital health tools with historically excluded end users in mind. As health care systems expand digital tool adoption, they must distinguish fundamental skill gaps from usability barriers, as each may require different intervention strategies.
10 May 2026
Read appraisal →JMIR mHealth and uHealth
mHealth-Based Gamification Interventions to Promote Health Among Older Adults: Scoping Review
BACKGROUND: Healthy aging has emerged as a global priority. However, older adults' participation in health promotion programs remains low, and traditional health promotion models have achieved limited success in fostering sustained engagement among this population. Mobile health (mHealth)-based gamification interventions offer a promising way to address these challenges. However, no published reviews support or oppose the use of mHealth-based gamification interventions as health promotion strategies in older adults. OBJECTIVE: The study aimed to identify mHealth interventions using gamification to promote health among older adults. METHODS: Our scoping review was conducted following the Joanna Briggs Institute recommendations for scoping reviews and Arksey and O'Malley's framework. The process followed PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines and PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Literature Search Extension) checklist. A comprehensive literature search was conducted across 8 databases: PubMed, Scopus, Web of Science, Embase, Cochrane Library, CINAHL, PsycARTICLES, and IEEE Xplore Digital Library, from their inception to December 10, 2025. Two reviewers independently screened titles, abstracts, and full texts via Rayyan, with disagreements resolved by a third reviewer. RESULTS: This scoping review identified 11 studies. Only 1 article was published before 2022. The interventions were found to improve enjoyment and motivation (n=5), cognitive function (n=3), physical activity (n=2), and digital literacy (n=2). Individual studies also reported improvements in mental health (n=1) and adherence (n=1), a reduction in suicidal ideation (n=1), improvements in physical function (n=1), the promotion of social engagement (n=1), and the identification of mild cognitive impairment (n=1). Game elements used were ranked by frequency as progress, challenges, goals, levels, reward, sensation, storytelling or narration, leaderboard, surprise, and avatar. No research was found to use the game element of "social sharing." mHealth types included augmented and virtual reality-based training systems, wearable devices, mobile phones, tablets, and Windows platforms and devices. Notably, only 4 studies applied theoretical frameworks, and 3 omitted the concrete approach to gamification. CONCLUSIONS: As the first scoping review to identify and map mHealth-based gamification interventions for older adults, this study highlights their potential as an innovative approach to health promotion. By systematically synthesizing evidence regarding intervention designs, gamification strategies, and preliminary health outcomes, it establishes a foundation for future inquiry. However, this review is limited by the small number of included studies, precluding broad generalizations. Future research should assess long-term impacts, integrate theoretical frameworks, establish reporting guidelines, design personalized social-interactive interventions, and expand to broader health domains. Ultimately, these insights provide targeted guidance for developing age-appropriate digital health solutions, contributing to the realization of active aging.
10 May 2026
Read appraisal →Human vaccines & immunotherapeutics
Incidence of Bacille Calmette-Guérin associated lymphadenitis in healthy children: A systematic review and meta-analysis
Few systematic reviews or meta-analyses have addressed on the incidence of Bacille Calmette-Guérin (BCG) lymphadenitis in healthy children. A systematic literature search was independently conducted by two researchers using four English and Korean databases (PubMed, Scopus, KMbase, RISS). The risk of bias was assessed. A total of 52 peer-reviewed journal articles (about 1.8 million children) were included in meta-analyses. The incidence proportion of BCG lymphadenitis ranged from 0.0% to 25.6%. The pooled incidence proportion was 2.5% (95% CI, 1.6-3.6; I2 = 99%). Studies employing active (vs. passive) surveillance reported a significantly higher incidence proportion of lymphadenitis, as did randomized controlled trials (vs. prospective and retrospective cohort studies). Also, the incidence significantly differed according to study quality, publication period, and BCG strain. This study highlights substantial variability in the incidence of BCG lymphadenitis among diverse studies and underscores the influence of surveillance methods, study design, and vaccine strain on reported outcomes.
10 May 2026
Read appraisal →Annals of medicine
A comprehensive review of regulatory mechanisms of novel enterotoxin genes in Staphylococcus aureus from meat sources
BACKGROUND AND AIMS: Meat-borne Staphylococcus aureus (S. aureus) remains a leading global foodborne pathogen harbouring novel enterotoxin genes (NEGs) encoding superantigenic toxins with conditionally enhanced pathogenicity, representing a critical food safety hazard. This review characterizes NEG features, pathogenic mechanisms, multi-layered regulatory networks, and identifies key research challenges. METHODS: We systematically searched PubMed, Embase and the Web of Science Core Collection to synthesize molecular and multi-omics evidence (ChIP-seq, RNA-seq, CRISPR-Cas9) characterizing NEG classification, pathogenic mechanisms, multi-level regulatory networks (transcriptional, post-translational, environmental), and geographical distribution patterns in meat-derived S. aureus. RESULTS: NEGs comprise superantigenic and tissue-targeting subgroups mediating pathogenicity via cytotoxicity, intestinal microenvironment disruption, and immune evasion. Regulation involves a complex network of Agr/σB/SarA/Rot-mediated transcriptional control, phosphorylation/lactylation modifications and environmental sensing, exhibiting marked geographical divergence. Current limitations include technical resolution constraints, insufficient physiological model fidelity and incomplete regulatory crosstalk elucidation. CONCLUSIONS: Future research should prioritize transcription factor interaction mechanisms, growth-toxin correlation prediction models and multi-omics-based network decipherment. This review provides a foundational framework for NEG research to inform food safety risk assessment and targeted contamination control strategies.
10 May 2026
Read appraisal →Clinical oral investigations
Does endodontic treatment modify serum inflammatory markers of cardiovascular risk in individuals with asymptomatic apical periodontitis? a systematic review and meta-analysis.
OBJECTIVE: Plasma inflammatory biomarkers linked to cardiovascular risk have been associated with asymptomatic apical periodontitis. However, it remains unclear whether endodontic treatment can reverse these alterations. This review evaluated the effect of endodontic treatment on inflammatory markers in individuals with asymptomatic apical periodontitis. MATERIALS AND METHODS: A comprehensive search was conducted in PubMed/Medline, Embase, Web of Science, Scopus, VHL, gray literature, and reference lists between October and November 2022, with an update in September 2025. Risk of bias was assessed using the Newcastle-Ottawa Scale, and the certainty of evidence using the GRADE approach. Random-effects meta-analysis estimated pooled mean differences (MD) and 95% confidence intervals (95%CI) for serum inflammatory markers concentrations between treated individuals and controls (α = 5%). RESULTS: The search identified 6,295 records; sixteen studies were assessed and eight included in the quantitative synthesis. All studies showed moderate risk of bias, and evidence certainty was very low. Meta-analysis suggested possible reductions in C-reactive protein (CRP) [MD = 0.76 (95% CI: - 0.15, 1.67)] , interleukin-6 (IL-6) [MD = 0.81 (95% CI:-0.27, 1.90)], and tumor necrosis factor-alpha (TNF-α) [MD = 1.04 (95% CI:-0.38, 2.46)] after endodontic treatment, with levels similar to control groups. CONCLUSION: Evidence, although limited, suggests endodontic treatment may lower serum CRP, IL-6, and TNF-α levels in asymptomatic apical periodontitis patients. CLINICAL RELEVANCE: Endodontic treatment of asymptomatic apical periodontitis may help reduce systemic inflammatory biomarkers associated with cardiovascular risk, reinforcing its potential role beyond local infection control.
10 May 2026
Read appraisal →The British journal of psychiatry : the journal of mental science
Characterisation of serious mental illness trajectories through transdiagnostic clinical features
BACKGROUND: Electronic health records (EHRs), increasingly available in low- and middle-income countries (LMICs), provide an opportunity to study transdiagnostic features of serious mental illness (SMI) and its trajectories. AIMS: Characterise transdiagnostic features and diagnostic trajectories of SMI using an EHR database in an LMIC institution. METHOD: We conducted a retrospective cohort study using EHRs from 2005-2022 at Clínica San Juan de Dios Manizales, a specialised mental health facility in Colombia, including 22 447 patients with schizophrenia (SCZ), bipolar disorder (BPD) or severe/recurrent major depressive disorder (MDD). Using diagnostic codes and clinical notes, we analysed the frequency of suicidality and psychosis across diagnoses, patterns of diagnostic switching and the accumulation of comorbidities. Mixed-effect logistic regression was used to identify factors influencing diagnostic stability. RESULTS: High frequencies of suicidality and psychosis were observed across diagnoses of SCZ, BPD and MDD. Most patients (64%) received multiple diagnoses over time, including switches between primary SMI diagnoses (19%), diagnostic comorbidities (30%) or both (15%). Predictors of diagnostic switching included mentions of delusions (odds ratio = 1.47, 95% CI 1.34-1.61), prior diagnostic switching (odds ratio = 4.01, 95% CI 3.7-4.34) and time in treatment, independent of age (log of visit number; odds ratio = 0.57, 95% CI 0.54-0.61). Over 80% of patients reached diagnostic stability within 6 years of their first record. CONCLUSIONS: Integrating structured and unstructured EHR data reveals transdiagnostic patterns in SMI and predictors of disease trajectories, highlighting the potential of EHR-based tools for research and precision psychiatry in LMICs.
9 May 2026
Read appraisal →Accident; analysis and prevention
Which approach better samples extreme traffic conflicts? Conventional- vs. machine learning-based sampling methods.
Extreme value theory has been receiving much attention of late for proactively estimating crash risk through a two-step procedure that first samples extreme traffic conflicts and then estimates crash risk based on those sampled extremes. Although the existing body of research has encapsulated sampling methods within a predominant conventional technique, there is no universally accepted practice on how to efficiently select threshold values, nor on how to evaluate the sampled extreme conflicts alignment with the conceptual crash severity level framework. This research aims to address these issues by employing machine learning-based sampling methods, which do not require predefined thresholds, and by comparing the sampled extremes with the conceptual severity levels, to assess their alignment. After a review of recent developments in machine learning techniques in transportation and other engineering fields, two promising machine learning sampling models, autoencoder neural network and isolation forest, were investigated using a database of vehicle-to-pedestrian conflicts at urban signalized intersections. Sampled extreme conflicts using the machine learning and conventional sampling techniques-as a baseline -were assessed and compared using two criteria: their visual alignment with the conceptual severity level framework, and their compatibility with the extreme value distribution. The results demonstrate that the extreme conflicts selected based on the machine learning methods better mirror the conceptual severity levels than the conventional sampling technique. Moreover, extremes classified by the isolation forest more closely preserve the characteristics of the empirical tail distributions, demonstrating a better contextual representation for modeling with the extreme value distribution compared to the autoencoder neural network and conventional sampling methods.
9 May 2026
Read appraisal →Computer methods in biomechanics and biomedical engineering
Modified mutual information feature selection algorithm to predict COVID-19 using clinical data
The COVID-19 pandemic has profoundly impacted health, emphasizing the need for timely disease detection. Blood tests have become key diagnostic tools due to the virus's effects on blood composition. Accurate COVID-19 prediction through machine learning requires selecting relevant features, as irrelevant features can lower classification accuracy. This study proposes Modified Mutual Information (MMI) for feature selection, ranking features by relevance and using backtracking to find the optimal subset. Support Vector Machines (SVM) are then used for classification. Results show that MMI with SVM achieves 95% accuracy, outperforming other methods, and demonstrates strong generalizability on various benchmark datasets.
6 May 2026
Read appraisal →Journal of medical virology
A Triage Model for HR-HPV Positive Women Based on Methylation of Human and HPV Genes
The aim of this study is to develop a machine learning triage model for HR-HPV positive women based on methylation patterns of human and HPV genes to predict the risk of CIN2 +, and to compare its performance with traditional detection techniques. A total of 512 eligible women participated in the study, with exfoliated cervical cell specimens collected for methylation analysis of both human and HPV genes. Highly methylated gene fragments related to cervical cancer were identified through high density, high association, high MHL (Methylation Haplotype Load) screening and Logistic regression. The samples were divided into a training set and a validation set at a ratio of 7:3, and a machine learning triage model was constructed using CIN2+ as the outcome. Among 512 HR-HPV positive women, 174 (34.0%) had CIN2 +. To construct the random forest model, 10 high methylation human gene fragments were identified from a pool of 45 genes, along with HPV 16, 18, and 52 L2 genes. In the validation set, the random forest model identified 45 samples as positive (38 were true positives) and 112 samples as negative (96 were true negatives). The model achieved an AUC of 0.9, and DeLong test confirmed its performance was significantly superior (p < 0.001) to HPV 16/18 genotyping and cytology testing. The random forest model constructed based on methylation patterns of human and HPV genes demonstrated strong predictive efficacy for CIN2+ in HR-HPV positive women, and may optimize the triage method in cervical cancer screening.
5 May 2026
Read appraisal →Microvascular research
OPU-NET-DADENA: Optimized deep learning ensemble with u-net segmentation for early detection of diabetic retinopathy
One of the most significant microvascular complications of diabetes mellitus (DM) is diabetic retinopathy (DR). In the early stages, patients with DR may not exhibit any noticeable symptoms. It is a diabetic disorder that damages retinal blood vessels in the eyes. At first, there are no symptoms or sporadic visual issues. When it worsens, it affects both eyes and can lead to partial or total blindness. A person who already has DM is therefore constantly at a higher risk of developing the condition. Early identification can prevent the possibility of total and irreversible blindness. Therefore, needs an efficient and early diagnosis system. So, this paper proposes a new deep-learning methodology in a specific Deep Siamese DenseNet for early detection of DR. The proposed method is accomplished through various steps, such as Data Collection, Preprocessing, Augmentation, Segmentation, Feature Extraction, Feature Selection, and Detection. An adaptive histogram equalization approach named Contrast Limited Adaptive Histogram Equalization (CLAHE) is used to preprocess input images, which reduces amplification of noise. Then, the segmentation is done by the Optimized U-NETs. Next, features of the contrasted retinal images are extracted by residual attention EfficientNet (RA-EfficientNet). Then, the optimal features are selected by a hybrid Reptile Search Algorithm (RORS). Finally, the deep learning methodology includes DarkNet, DenseNet 201, and NasNetMobile used to detect diabetic retinopathy at an early stage. The model is implemented in MATLAB and evaluated using accuracy, precision, F-score, specificity, sensitivity, MCC, NPV, FPR, and FNR. The proposed approach achieves 99.33% accuracy and 98.32% precision, outperforming previous methods that reported accuracies of 95-97% and precisions of 94-96%, demonstrating its effectiveness for reliable early detection of DR.
5 May 2026
Read appraisal →Journal of diabetes science and technology
Diabetes-Technology and Waste: The Future is Now.
The downside of the success story of diabetes technology is the amount of waste generated by manufacturing and using such medical products. Quantitative surveys performed in the United States and Germany document how many pounds of plastic waste, batteries, and electronic parts are piling up per patient with diabetes each year; however, the actual environmental burden of diabetes care has not been assessed yet. Given the highly probable further increase in usage of diabetes technology devices, what are the options to change the situation? Ideally, one would avoid generating waste by optimizing the design of the products (Eco-Design); however, this approach faces a number of complex regulatory and economic hurdles. The issue of waste management is becoming increasingly important as the use of wearable devices increases. Stewardship of the environment will require all stakeholders to address waste management.
4 May 2026
Read appraisal →Environmental science. Processes & impacts
Machine learning-driven QSAR models for the prediction of metabolic mechanisms and thyroid hormone-disrupting effects of emerging pollutants in the human body: a case study of bisphenol analogues
Research on theoretical prediction methods for elucidating the reaction mechanisms and thyroid hormone-disrupting effects of emerging pollutants in the human body faces significant challenges. The application of in silico methods utilizing machine learning is increasingly recognized as an effective strategy to determine the mechanisms of reactions catalyzed by human cytochrome P450 enzymes (CYPs) and to predict the adverse effects of emerging pollutants. Bisphenol analogues (BPs) represent one of the most important endocrine disruptors. These compounds can cause serious effects on the ecological environment and human health. Herein, density functional theory (DFT) calculations was employed to investigate the reaction mechanisms of the O-addition and H-abstraction of 20 BPs by human CYPs. A machine-learning-integrated quantitative structure-activity relationship (ML-QSAR) framework was established to predict the energy barriers of three types of reactions. Moreover, binding affinities were calculated between BPs (including their metabolites) and TRβ-LBD to evaluate their thyroid hormone-disrupting effects. The binding affinity data of BPs to TRβ-LBD were used as a training set to develop a ML-QSAR model for efficient prediction of potentially hazardous BPs. A ML-QSAR model with an R2 of 0.869 was established to predict their thyroid hormone-disrupting effects. The study enhances our understanding of CYP catalytic mechanisms involving BPs and provides a reference for the future design of environmentally friendly BPs. The predictive model developed for thyroid hormone-disrupting effects can aid in identifying the adverse effects of emerging BPs, supporting more effective management of toxic compounds.
4 May 2026
Read appraisal →Environmental science. Processes & impacts
Adverse outcome pathway-informed machine learning for predicting vascular toxicity of emerging organic pollutants
Emerging organic pollutants (EOPs) are increasingly detected in wastewater and pose potential vascular toxicity risks that remain inadequately assessed in current regulatory frameworks. This study developed an adverse outcome pathway (AOP)-informed machine learning approach to evaluate vascular toxicity for 312 EOPs. By integrating ToxCast high-throughput bioassay data with Morgan fingerprints, we trained fourteen multilayer perceptron (MLP) models targeting key events in AOP 509, including Nrf2 inhibition, oxidative stress, mitochondrial dysfunction, apoptosis, endothelial impairment, and angiogenesis disruption. Our optimized models achieved high predictive accuracy (70-95%), enabling activity classification for both tested and untested chemicals. The predicted activation profiles prioritized chemicals such as ketoconazole, sertraline, and miconazole, with literature evidence supporting their vascular toxicity potential. This AOP-guided modelling framework demonstrates how integrating mechanistic pathways with machine learning can inform chemical risk assessment and prioritization, supporting hazard evaluation and environmental decision-making for pollutants with limited toxicological data.
4 May 2026
Read appraisal →Journal of proteome research
Stability-Based Machine Learning Identifies a Minimal Two-Protein Serum Signature for Early Silicosis
BACKGROUND: The early diagnosis of silicosis, an irreversible fibrotic lung disease, is challenged by the low sensitivity of current radiological methods in early-stage disease and their susceptibility to interobserver variability. Consequently, a pressing need exists for noninvasive, objective biomarkers to facilitate timely detection and intervention. METHODS: We employed a multistage study design comprising a discovery cohort (57 Stage I silicosis patients, 57 matched controls) and an independent, unmatched validation cohort (40 patients, 40 controls). Serum protein profiles were generated using Olink targeted proteomics. We utilized a rigorous, stability-based machine learning framework, which integrated Lasso, Random Forest, and SVM-RFE algorithms over 100 iterations, to perform feature selection and identify a robust biomarker signature from the discovery cohort. Based on the selected features, a logistic regression model was subsequently constructed, and its performance was evaluated using both internal and external validation. RESULTS: Our discovery strategy identified a two-protein signature comprising IL8 and CCL3. This signature demonstrated excellent diagnostic performance in the discovery cohort, achieving a cross-validation AUC of 0.986 (95% CI: 0.975-1.000). Importantly, the model's robustness was confirmed in the heterogeneous validation cohort, where it achieved an outstanding AUC of 0.973 (95% CI: 0.936-1.000), with 95.0% specificity and 77.5% sensitivity. Bioinformatic analysis revealed that decreased serum levels of IL8 and CCL3 were associated with silicosis, providing novel diagnostic biomarkers and highlighting a complex, paradoxical shift in circulating chemokines during early-stage disease.
4 May 2026
Read appraisal →Journal of occupational and environmental medicine
Combining MEA-Net and LAP-Net for Pneumoconiosis Staging Framework
OBJECTIVE: Pneumoconiosis is a common and highly hazardous occupational disease. The staging of pneumoconiosis is mainly carried out by experienced doctors on the basis of the shadows and textures on lung x-ray films. Despite well-defined criteria, the process remains influenced by individual clinical judgment. METHODS: To improve the subjective process of pneumoconiosis diagnosis, this study proposes a new deep learning framework for pneumoconiosis staging framework using MEA-Net and LAP-Net. RESULTS: The experimental results show that the accuracy, precision, recall, specificity, F1-score, and area under the curve in the four-stage classification reached 95.24%, 95.15%, 95.15%, 90.58%, 94.85%, and 98.87%, respectively. CONCLUSION: The proposed method can help doctors to identify the different stages of pneumoconiosis more accurately in the diagnosis of the disease.
4 May 2026
Read appraisal →Advances in colloid and interface science
Electrospun nanofibrous membranes for self-powered wearable air filtration systems
With the growth of society and industrialization, air pollution has intensified, disturbing the ecological balance and presenting considerable risks to human health. The development of intelligent wearable protective systems is a major breakthrough in real-time health monitoring and prevention, greatly improving personal health management outcomes. An optimal smart air filtration system must demonstrate reliable filtration efficiency, minimal air resistance, and incorporate features for health monitoring and interaction with users. As a result, it is essential to create innovative materials for air filtration that can effectively trap particulate matter (PM). The adaptability, high surface area, interconnected porosity, and configurable morphology of electrospun nanofibers make them a highly promising platform for developing high-performance air filtration media. The conversion of ambient mechanical vibrations into electrical power by piezoelectric and triboelectric nanogenerators (PENGs and TENGs) has emerged as a practical strategy for effective energy harvesting. Integrating self-powered technologies with fibrous air filtration materials to efficiently eliminate fine particulate matter provides a new and sustainable approach to air purification. This review systematically summarizes recent advances in electrospun nanofibrous membranes for self-powered, intelligent, wearable air filtration systems. It begins with an analysis of the fundamental mechanisms of air filtration, the criteria for performance evaluation, and the principles of electrospinning technology. Subsequently, the practical application performance of these filtration systems is critically examined. Finally, the review outlines prospective research directions and discusses the remaining challenges confronting self-powered air filtration systems.
4 May 2026
Read appraisal →PloS one
Optimizing LSTM networks and feature selection algorithms using GEE data
Feature selection uncertainty and suboptimal model configuration in flood susceptibility mapping (FSM) are critical challenges for disaster risk reduction. This study introduces a novel integrated framework that couples feature selection strategy with metaheuristic-optimized deep learning for high-precision FSM in the flood-prone Khuzestan Province, Iran. An initial set of 19 factors was sourced from Google Earth Engine (GEE). The most influential variables were identified using an ensemble of nine feature selection methods, including Boruta, Boruta-SHAP, Elastic-Net, Mutual Information, Permutation Importance, Recursive Feature Elimination (RFE), Sequential Forward Selection (SFS), Stability Selection, and Deep Feature Importance. For model development, 1,000 sample points were used, consisting of 500 randomly selected non-flood points (value 0) and 500 flood points (value 1), with the trained model subsequently generalized to the entire study area. In this process, a frequency-based consensus rule was applied, whereby variables were retained only if selected by a majority of methods. This process established the Normalized Difference Vegetation Index (NDVI) and Daily Minimum Temperature (TMMN) as the most critical predictors. A Long Short-Term Memory (LSTM) was developed using this optimal feature set and subsequently enhanced through hyperparameter optimization with five advanced metaheuristic algorithms, including WOA, GWO, OOA, CSA, and HOA. The model validation demonstrated that optimization significantly boosted performance, with the LSTM-WOA model emerging as superior, achieving the highest F1-Score (0.88) and Cohen's Kappa (0.75). The final FSM identified the northwestern and central regions as the highest susceptibility. The study innovation lies in its formalized consensus feature selection and comparative metaheuristic optimization, providing a reliable tool for FSM in arid and semi-arid regions.
3 May 2026
Read appraisal →PloS one
Auditing the impact of social media's policy shift on anti-vaccine discourse: A large language model-driven empirical study
The sudden termination of X's (formerly Twitter) misinformation policy on November 23, 2022, provides an opportunity to assess the effects of lifting content moderation restrictions on vaccine-related discourse. This study examines changes in the prevalence, thematic composition, and engagement of anti-vaccine discourse following X's policy shift, analyzing tweets from a seven-day period before and after the policy termination (November 16-30, 2022), excluding the announcement date itself from regression analyses. Using GPT-4o for stance classification, thematic categorization, and stance consistency assessment, with validation through external benchmarks and cross-annotator agreement, we find that anti-vaccine tweets increased significantly post-policy (OR = 1.60, 95% CI: 1.50-1.72), particularly via retweets, suggesting content amplification. Sensitivity analyses excluding highly retweeted content revealed that the policy change was also associated with increased creation of new anti-vaccine content. Thematically, health concerns over vaccination became more prominent, while conspiracy-related and anti-mandate narratives declined in relative prevalence. Stance consistency in quote tweets increased, indicating reinforced ideological alignment in anti-vaccine discourse. These results suggest that content moderation policies may constrain both the volume and amplification of anti-vaccine content, with policy removal associated with rapid shifts in discourse patterns.
3 May 2026
Read appraisal →JMIR aging
The Effectiveness of Digital Interventions to Increase Preventive Care Uptake in Older Adults: Systematic Review
BACKGROUND: Older adults face increasing health risks associated with aging and chronic disease; yet, uptake of recommended clinical preventive services remains low. Digital health interventions have the potential to enhance access and engagement, but their effectiveness in older adult populations remains unclear. OBJECTIVE: This systematic review aimed to examine the range and types of digital clinical preventive service interventions and assess their impact on preventive care uptake among older adults. METHODS: We conducted a systematic review of peer-reviewed research literature published since 2014. Eligible studies included experimental and quasi-experimental designs evaluating digital interventions targeting community-dwelling adults aged 60 years and older. Interventions focused on high-priority preventive services, including cancer screening and adult immunizations. Data were extracted using a standardized form and synthesized narratively due to heterogeneity in study designs and outcomes. RESULTS: In total, 24 studies involving over 1.3 million participants from 11 countries were included. Interventions used a range of digital tools, including telephone calls, SMS text messages, patient portals, and video-based education. While some digital and automated interventions demonstrated modest improvements in preventive services uptake, results were mixed. Interventions incorporating personalized elements (eg, tailored telephone counseling or in-person education) were generally more effective than generic, automated communications. Few studies reported on digital literacy support or intervention reach, and engagement with digital platforms was often low. CONCLUSIONS: Digital interventions can support modest improvements in preventive services uptake among older adults, particularly when personalized or combined with human interaction. However, assumptions of digital fluency and limited reporting on engagement constrain generalizability. Future research should prioritize inclusive design, detailed reporting, and strategies that address digital equity to better support older adult populations.
3 May 2026
Read appraisal →European respiratory review : an official journal of the European Respiratory Society
Rural versus urban living and COPD: a systematic review
Chronic obstructive pulmonary disease (COPD) is a leading cause of global morbidity and mortality. Emerging evidence suggests disparities in COPD outcomes between rural and urban populations, but no prior review has synthesised these differences globally. Five databases (Medline, Embase, Emcare, CINAHL and Cochrane Central) were searched in May 2025. Eligible peer-reviewed studies directly compared rural and urban populations in at least one of four measures of COPD burden: prevalence, symptom burden, exacerbations or mortality. Study quality was assessed and narrative synthesis was conducted due to heterogeneity in outcome measures. Of 1339 screened studies, 32 met inclusion criteria, spanning 13 countries. COPD prevalence was higher rurally in 83% (15/18) of studies, with 11/15 demonstrating statistical significance. This pattern was consistent across geographical distributions. Total exacerbation rates were higher rurally in 60% (3/5) of studies, although hospitalisations varied significantly. 50% (6/12) of studies reported higher hospitalisation rates in urban areas and 5/12 studies reporting higher rates in rural areas. 86% (6/7) of studies demonstrated higher mortality rurally and symptom burden was higher amongst rural residents in 67% (4/6) of studies; however, the majority of these were conducted in the USA. This review highlights consistent rural-urban inequalities in COPD prevalence and outcomes, reflecting the impact of healthcare inequities, socioeconomic deprivation and environmental exposures on COPD burden in rural areas. Targeted interventions promoting equitable healthcare access, health education, transition to cleaner fuels and rural access to smoking cessation and pulmonary rehabilitation services are essential to mitigate these disparities and improve outcomes in rural populations.
3 May 2026
Read appraisal →PloS one
Clinical manifestations of bed bug bites: A systematic review of case reports
IMPORTANCE: Clinical characterization of bed bug (Cimex spp.) bite manifestations remains limited. OBJECTIVE: This systematic review synthesizes case reports to describe dermatological, systemic, and psychological outcomes of bed bug bites. EVIDENCE REVIEW: Following PRISMA guidelines, multiple databases, including Pubmed and Scopus, were searched using terms such as "bed bug," "Cimex lectularius," "Cimex hemipterus," "case report," and "case series." Extracted data included demographics, species, lesion type, anatomical distribution, and clinical manifestations. Quantitative and qualitative analyses were conducted. RESULTS: Eighty-four patients were included: 76 with C. lectularius (90.5%) and, 8 with C. hemipterus (9.5%). Sex distribution was balanced (47.6% females, 52.4% males), and mean ages were similar (females 37.5 ± 22.1, males 42.3 ± 21.27 years; p = 0.332). Extremities were commonly affected, arms were reported in 71.4% of cases, legs in 59.5% and trunk in 34.5%. Psychological symptoms were registered in a handful of case reports (Anxiety 9.5%, Stress 9.5%, Hopelessness 9.5%). Systemic symptoms, generally associated with anemia, were reported in cases related to severe infestations in neglected patients. Some differences in systemic and local signs and symptoms were detected depending on age group. CONCLUSIONS: Bed bug bites predominantly affect exposed extremities, although with variable dermatologic patterns that can be confused with other arthropod bites. Psychological manifestations were reported in a small subset of cases, while systemic complications were rare.
3 May 2026
Read appraisal →PloS one
Prevalence of perinatal depression in Ethiopia: An umbrella review of systematic review and meta-analysis studies
BACKGROUND: Perinatal depression is a significant public health concern that affects women during pregnancy and the postpartum period. Despite being acknowledged globally, the burden of perinatal depression is particularly profound in low and middle-income countries, such as Ethiopia. This umbrella review is therefore intended to systematically consolidate findings on perinatal depression among Ethiopian women to better understand its prevalence, thereby highlighting the gaps in current research and informing future interventions. METHODS: This umbrella review used the PRIOR checklist for the reviews of systematic review and meta-analytic studies. The review protocol has been registered on PROSPERO: CRD42023495174. PubMed, EMBASE, and PsycINFO databases were searched for the presence of systematic review and meta-analysis studies. The quality of included articles has been evaluated with a measurement tool to assess systematic review and meta-analysis studies (AMSTAR). A novel graphic approach with an estimated corrected covered area (CCA) has been used to determine the degree of overlap of primary studies in the systematic review and meta-analysis studies. The weighted random effect model was used during the meta-analysis. RESULT: A total of 28 unique primary studies and 8 systematic reviews, and meta-analysis studies with 15,592 participants were included in this umbrella review. The pooled prevalence of perinatal depressive symptoms in the included systematic review and meta-analysis studies ranges from 20.1% to 25.8%. The pooled umbrella prevalence of perinatal depressive symptoms among women in Ethiopia was 22.49% (95 CI%:21.38, 23.59). The pooled umbrella analysis revealed that the antenatal and postnatal depressive symptoms were 22.76% (95% CI: 19.9, 25.62) and 21.75% (95% CI: 21.03, 22.48), respectively. In addition, the pooled prevalence of perinatal depression in studies that included 10 or below primary studies is 22.86% (95%CI:20.39, 25.33), and in those that included below 10 primary studies, it was 22.10% (95%CI: 21.55, 22.65). The novel graphic presentation depicted a very high degree of overlap of primary studies in the included systematic reviews and meta-analysis studies; corrected covered area (CCA) of 25.5%. Four of the included studies (fifty percent) had high methodological quality, and the remaining four relied on a moderate quality range. CONCLUSION: The pooled overall, antenatal, and postnatal prevalence of depression symptoms was high in Ethiopia, with no significant difference during the antenatal and postnatal period. An improved understanding of perinatal depression will therefore guide policymakers and health practitioners in developing targeted strategies to alleviate this mental health challenge.
3 May 2026
Read appraisal →Journal of medical Internet research
Rapid Deployment of Telemedicine in HIV Care: Mixed Methods Study of Providers' Attitudes and Perceptions
BACKGROUND: The COVID-19 pandemic prompted an abrupt transition to telemedicine for HIV care, necessitating the exploration of provider attitudes and experiences to understand its ongoing viability and impact. OBJECTIVE: This study aimed to assess providers' attitudes toward and experiences with telemedicine at HIV clinics in the Chicago area during the COVID-19 pandemic at 2 time points and at 2 clinical sites. METHODS: We conducted a convergent mixed methods study to evaluate and explore providers' attitudes toward and experiences with telemedicine at HIV clinics in the Chicago area during the COVID-19 pandemic, applying the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework and the updated Consolidated Framework for Implementation Research. This study assessed HIV providers via surveys at 2 time points, capturing responses on the acceptability, appropriateness, feasibility, and maintenance of telemedicine. Semistructured key informant interviews were conducted on a random selection of 10 participants to explore perceived experiences with telemedicine. RESULTS: Among emailed providers, 43 of 83 (51.8%) and 27 of 82 (32.9%) responded to survey 1 and survey 2, respectively. The first survey recorded telemedicine usage at 75%, which decreased to 58% by the second survey. Overall, the majority of respondents agreed with statements that assessed telemedicine as appropriate, acceptable, and feasible. There were overall few statistical differences in responses between sites, although more providers at the community site indicated at least some potential value in telemedicine when compared to providers at the university hospital (100% agree or strongly agree vs 82.3%; P=.04) in survey 1. In survey 1, providers with more than 10 years of experience were less likely to report telemedicine helped them see more patients (31.6% agree or strongly agree vs 70.6% for providers with ≤10 y of experience; P=.008). Fewer experienced providers felt they could talk about private issues with their patients during telemedicine (57.9% of more experienced vs 88.3% of less experienced providers; P=.03). Key informant interviews provided qualitative insights into telemedicine integration, revealing mixed sentiments; providers appreciated the flexibility and accessibility that telemedicine offered but preferred in-person visits for their thoroughness, especially for physical examinations and laboratory tests. Despite initial barriers such as technical challenges and patient preferences for in-person visits, telemedicine was deemed feasible for maintaining communication and care quality. Providers highlighted the need for better technological support and ongoing training to optimize telemedicine usage. CONCLUSIONS: Our study underscores telemedicine as a sustainable adjunct to traditional HIV care, emphasizing the importance of addressing technological and training barriers to enhance its efficacy.
3 May 2026
Read appraisal →JMIR formative research
Comparing Perceptions of ChatGPT Use in Health Attitude Contexts Among Users and Nonusers: Cross-Sectional Study
BACKGROUND: In light of the growing use of artificial intelligence (AI) in health care, individuals' access to and use of health information are transforming. ChatGPT, an AI chatbot, provides immediate responses to health queries, with the potential to influence health-related attitudes, thereby raising concerns related to privacy, reliability, and security. OBJECTIVE: This study aimed to investigate the perceived usefulness, risks, anxiety, and social influence of ChatGPT on health attitudes among users and nonusers in Saudi Arabia. METHODS: A cross-sectional study was conducted using an online survey based on a validated tool. In total, 337 participants aged 18 years and older responded to questions assessing their perceptions of ChatGPT on health-related attitudes. RESULTS: Data showed that 76.1% (194/255) of the respondents used ChatGPT, with the majority being younger and more highly educated. The main uses for health-related purposes were health education (43/194, 22.2%) and physical activity guidance (31/194, 16%). The analysis showed that users considered ChatGPT useful for health-related decisions, with 45.9% (89/194) finding it easy to learn and use, but concerns about privacy (106/194, 54.7%) and reliability (87/194, 44.9%) remained. Among nonusers, security risks (39/61, 63.9%) were the major barrier to using AI-based tools for health purposes, and 68.9% (42/61) found such tools attractive and engaging. There were no statistically significant differences between users and nonusers across all examined sociodemographic characteristics (P>.05). CONCLUSIONS: The study established the potential of ChatGPT in improving health decision-making and revealed cultural, privacy, and trust issues that may affect its implementation. These findings underscore the importance of strengthening the security of AI-based applications to enhance public acceptability of related health policies and to support the safe integration of tools such as ChatGPT into the health care system.
3 May 2026
Read appraisal →JMIR mHealth and uHealth
Alcohol Use Trajectories During the First 72 Weeks of WHOOP Wearable Platform Membership: Observational Cohort Study
Among 30,000 new wearable device users (11.6 million person-days), self-reported alcohol consumption significantly declined over 72 weeks, with the daily probability of drinking decreasing by 5.8 percentage points (P<.001) and reductions across age and biological sex.
2 May 2026
Read appraisal →The Cochrane database of systematic reviews
Vitamin D for preventing acute respiratory infections in children up to five years of age
RATIONALE: Acute respiratory infections (ARIs) are a leading cause of morbidity and mortality in children under five years of age and contribute to healthcare visits and hospitalisations globally. Vitamin D deficiency is common amongst pregnant women and young children. Given that vitamin D supplementation is safe, affordable, and easy to administer, its potential to reduce ARI-related healthcare visits holds substantial public health relevance. This review evaluates the benefit and harm of vitamin D supplementation in preventing ARI-related healthcare visits in young children, aiming to inform supplementation policies during pregnancy and early childhood. OBJECTIVES: To determine the benefit and harm of vitamin D supplementation for preventing ARIs in children up to five years of age. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, Web of Science, WHO Global Index Medicus, and four clinical trial registries on 18 March 2025. ELIGIBILITY CRITERIA: We included randomised controlled trials (RCTs) comparing vitamin D to placebo, or a higher dose (≥ 1000 IU) versus a lower dose (≤ 1000 IU) administered from early pregnancy through to five years of age. We excluded studies involving children with chronic respiratory or systemic conditions. OUTCOMES: Critical outcomes: 1) healthcare visits made by children for an ARI: (a) the proportion of children with healthcare visits made for ARIs; (b) the mean number of healthcare visits made for ARIs per child; and 2) hypercalcaemia: the number of pregnant women and children with hypercalcaemia. RISK OF BIAS: We assessed risk of bias using the Cochrane risk of bias (RoB) 1 tool for outcomes reported in the summary of findings tables. SYNTHESIS METHODS: We synthesised outcome data using meta-analyses, calculating risk ratios (RR) for dichotomous, and mean differences (MD) for continuous outcomes, each with 95% confidence intervals (CI). Where meta-analysis was not feasible, we summarised the results narratively. We used GRADE to assess the certainty of the evidence for pre-specified outcomes. INCLUDED STUDIES: We included 107 RCTs involving 31,521 participants. Vitamin D supplementation was administered during pregnancy, early childhood, or both, and in some cases to both infants and lactating mothers. Interventions used vitamin D2, D3, both, or unspecified forms, with dosages ranging from daily administration to large single or quarterly boluses. Most were delivered orally, typically on a daily schedule, but also weekly or quarterly, over durations ranging from a single dose to 18 months. Settings included hospitals, day-care centres, communities, and homes. SYNTHESIS OF RESULTS: Vitamin D supplementation may result in a slight reduction in the proportion of children who make ARI-related healthcare visits compared to placebo (risk ratio (RR) 0.95, 95% confidence interval (CI) 0.91 to 1.00; P = 0.03; 10 studies, 2447 participants; low-certainty evidence), but probably does not reduce the mean number of ARI-related healthcare visits per child (mean difference (MD) 0.07, 95% CI -0.06 to 0.20; P = 0.32; 3 studies, 561 participants; moderate-certainty evidence). Comparisons between higher and lower doses of vitamin D probably do not reduce the proportion of children making ARI-related healthcare visits (RR 0.94, 95% CI 0.81 to 1.10; P = 0.46; 2 studies, 1382 participants; moderate-certainty evidence), and do not reduce the mean number of ARI-related healthcare visits per child (MD -0.10, 95% CI -0.59 to 0.39; P = 0.69; 1 study, 579 participants; low-certainty evidence). No cases of hypercalcaemia were reported among pregnant women in trials comparing vitamin D supplementation with placebo. In higher versus lower dose comparisons, supplementation may result in little to no difference in the risk of hypercalcaemia among pregnant women (RR 1.61, 95% CI 0.60 to 4.31; P = 0.34; 6 studies, 2379 participants; low-certainty evidence). Similarly, the evidence that vitamin D supplementation has little to no effect on the risk of hypercalcaemia in children, when compared with placebo, is very uncertain (RR 0.81, 95% CI 0.53 to 1.24; 7 studies, 1542 participants; very low-certainty evidence) and may result in little to no difference in the risk of hypercalcaemia in children when higher doses are compared to lower doses (RR 1.23, 95% CI 0.82 to 1.85; 7 studies, 1287 participants; low-certainty evidence). AUTHORS' CONCLUSIONS: We found low-certainty evidence that vitamin D supplementation during pregnancy or early childhood may result in a slight reduction in the proportion of children under five years of age who make ARI-related healthcare visits, but probably does not reduce the mean number of healthcare visits for ARIs per child. This finding highlights the need for large, well-designed, placebo-controlled trials to confirm the potential benefit. We found moderate-certainty evidence that higher-dose vitamin D supplementation, compared with lower doses, probably does not reduce the proportion of children making healthcare visits for ARIs and does not reduce the mean number of ARI-related healthcare visits per child. Hypercalcaemia occurs infrequently in both pregnant women and children receiving vitamin D supplementation. Where hypercalcaemia could be measured, specifically in children receiving vitamin D versus placebo, vitamin D supplementation may have little to no effect on the risk of hypercalcaemia (very low-certainty evidence). In both children and pregnant women, a higher dose of vitamin D compared to a lower dose may result in little to no difference in the risk of hypercalcaemia (low-certainty evidence). FUNDING: This Cochrane review had no dedicated funding. REGISTRATION: Protocol (2022) DOI: 10.1002/14651858.CD015111.
2 May 2026
Read appraisal →Journal of chemical information and modeling
Development, Evaluation and Application of a Multi-Representation Fusion Model for Accurate Prediction of Per- and Polyfluoroalkyl Substance (PFAS) Binding to Plasma Proteins
Per- and polyfluoroalkyl substances (PFAS) constitute a large and structurally diverse class of man-made chemicals. Their strong carbon-fluorine (C-F) bonds confer high environmental persistence, bioaccumulation, and various associated toxicities. As amphiphilic compounds, most PFAS bind to proteins and accumulate in protein-rich tissues, with such bioaccumulation exerting significant adverse impacts on human health. Accurate evaluation of the binding status between PFAS and proteins constitutes an essential step in health risk assessment. Traditional experiments and certain modeling approaches for analyzing PFAS bioaccumulation suffer from drawbacks such as time-consuming processes, high costs, or inadequate capture of molecular structural information, while existing machine learning-based prediction methods rely on single molecular representation, making it difficult to comprehensively encode the structural information on PFAS. Here, we propose MURNet, a multirepresentation fusion network model integrating chemical descriptors, 2D molecular graphs, and molecular fingerprints to predict PFAS-plasma protein binding. Compared with the state-of-the-art baseline models, MURNet achieves the optimal comprehensive performance. The multirepresentation fusion strategy generates higher-quality molecular features. Tanimoto similarity applicability domain analysis demonstrates MURNet's capability to reliably predict PFAS homologues. Case studies reveal the effectiveness of MURNet in screening PFAS with potential binding affinity to human serum albumin (HSA).
2 May 2026
Read appraisal →Lancet (London, England)
Safety and efficacy of the monoclonal antibody L9LS for malaria prevention in children exposed to perennial malaria transmission in Kenya: a randomised, double-blind, placebo-controlled, phase 2 trial
BACKGROUND: Malaria remains a major cause of mortality globally, especially among young children in sub-Saharan Africa. The long-acting monoclonal antibody L9LS has shown high efficacy in preventing malaria in children aged 6-10 years exposed to seasonal transmission but remains untested in perennial transmission settings and younger children. We assessed the safety, tolerability, and efficacy of L9LS in infants and children in a high perennial malaria transmission setting. METHODS: This double-blind, two-part, randomised, placebo-controlled, phase 2 trial was done in Siaya county in western Kenya. In parts 1a and 1b, we tested the safety and tolerability of L9LS using an age de-escalation and dose escalation approach and randomly assigned (3:1) cohorts of healthy children (three cohorts aged 5-10 years, three cohorts aged 5-59 months, and two cohorts aged 5-71 months) to L9LS at doses of 5, 10, 20, 30, or 40 mg/kg subcutaneously or to placebo (normal saline). In part 2, healthy children aged 5-59 months were randomly assigned (1:1:1) by use of centralised computer-generated lists to receive two doses of L9LS at 10-20 mg/kg at baseline and month 6, one dose of L9LS at baseline and placebo at month 6, or placebo at both timepoints. Children were followed up for 12 months with monthly clinic visits and blood smear collections. Primary safety outcomes were incidence and severity of local and systemic solicited adverse events within 7 days of dosing and serious adverse events throughout follow-up. The primary efficacy endpoint was Plasmodium falciparum infection detected by blood smear over 12 months. Primary analyses were done in the modified intention-to-treat population, consisting of all randomly assigned participants who received the study intervention. This trial is registered with ClinicalTrials.gov (NCT05400655) and is complete. FINDINGS: In parts 1a and 1b, 96 children were enrolled and randomly assigned between Oct 1, 2022, and Jan 16, 2024; 72 participants were assigned to L9LS and 24 were assigned to placebo. In part 2, 324 children aged 5-59 months were enrolled and randomly assigned between Jan 26 and June 2, 2023; 108 children were assigned to one-dose L9LS, 106 to two-dose L9LS, and 110 to placebo. Across all study parts, grade 3 or worse treatment-related adverse events occurred after four (1%) of 384 L9LS injections and two (1%) of 338 placebo injections; these events all resolved by study end. The proportion of solicited and unsolicited adverse events was similar across all L9LS dose groups. There were no serious adverse events related to the trial. In part 2, 70 (66%) of 106 children in the two-dose L9LS group had at least one P falciparum infection during the 12-month follow-up versus 91 (83%) of 110 children in the placebo group (protective efficacy 42·7%, 95% CI 22·5-57·7; p=0·0003). INTERPRETATION: L9LS was protective against malaria in young children in western Kenya without evident safety concerns over 6-12 months. A higher dose of L9LS might be needed to achieve high-level efficacy against malaria in young children exposed to intense perennial P falciparum transmission. FUNDING: Gates Foundation.
2 May 2026
Read appraisal →PloS one
Gender disparities in Italian academic medicine: A cross-sectional study of clinicians in the 2024 stanford top 2% scientists database
BACKGROUND: Women remain underrepresented in senior and influential research positions despite gradual improvements over recent decades.The aim of this study was to assess gender representation among highly cited Italian clinical scientists and to examine differences across academic fields, institutions, and geographic regions. METHODS: We conducted a cross-sectional analysis of Italian clinical scientists included in the 2024 Stanford Top 2 Percent Scientists database. Gender was determined from given names, and demographic and academic information was obtained from national physician registries and publicly available curriculum vitae. Characteristics were compared by gender, and a logistic regression model was used to examine factors associated with female representation. RESULTS: A total of 3389 clinical scientists were identified, of whom 824 were women. Women represented approximately one quarter of highly cited Italian clinical researchers. They were younger and had more recent years of first publication compared with men. No significant gender differences were observed in academic affiliation or geographic distribution. Representation varied across fields, with surgical specialties demonstrating the lowest proportions of women and toxicology the highest. However, in most disciplines, representation converged toward the overall average when sample sizes increased, indicating that academic fields alone contributed minimally to gender representation. In the multivariable model, only toxicology showed significantly greater female representation, while more recent year of first publication was independently associated with being a woman.. CONCLUSIONS: Women remain underrepresented among highly cited Italian clinical scientists, despite evidence of gradual improvement in representation over time. The limited influence of academic fields suggests that broader structural and cultural factors likely contribute to these gaps. These findings highlight the need for targeted strategies to promote equal representation and support the career advancement of women in academic medicine.
28 Apr 2026
Read appraisal →BMJ mental health
Using electronic health records to evaluate a children and young people's social prescribing service: challenges and implications for research and practice
BACKGROUND: Preliminary evidence indicates that social prescribing (SP) can improve children and young people's (CYP) well-being but is limited by small non-representative samples and often relies on descriptive statistics. Given the wide implementation of SP in the UK, administrative records provide a unique opportunity to understand current practice and assess impacts on well-being. OBJECTIVES: (1) To understand the quality of data captured in SP administrative records. (2) To explore which CYP are currently receiving SP and what SP entails in practice. (3) To assess the impact of SP on well-being. METHODS: We used administrative records from one CYP SP service in England. Records were extracted from Joy, an online platform for managing SP. Over 18 months, 770 age-eligible CYP were referred to SP, 203 of whom were successfully discharged and completed two pre-post measures of well-being (the short Warwick-Edinburgh Mental Wellbeing Scale; SWEMWBS) at least 7 days apart. We used descriptive statistics, a paired t-test to assess changes in well-being and linear regressions with interactions to test effect modification. FINDINGS: Missing data was the largest issue, with ethnicity missing for 94% of CYP. A lack of detail and inconsistent recording for both individual characteristics and SP practices also presented challenges. Despite this, we identified that most CYP were referred by their GP, followed by their school, with 97% referred because of their mental health. The most common pathway was to receive SP for around 90 days, with 10-15 link worker contacts and 6 contact hours. Following SP, SWEMWBS scores improved by 3.72 points (t(202)=17.50, 95% CI 3.30 to 4.14, p<0.001), a 20% relative increase. Exploratory analyses suggested that this increase was greater for those with lower baseline well-being. CONCLUSIONS: Despite numerous challenges with missing data and data quality, we found that CYP well-being increases following SP (as it is currently implemented). The moderate effect size was consistent with larger studies of adults. CLINICAL IMPLICATIONS: Further development of online platforms is needed to monitor access to, nature of and efficacy of SP. For those working in SP, we recommend more training, implementation of standardised guidelines and designated time to update records.
27 Apr 2026
Read appraisal →BMJ health & care informatics
i-MoMCARE: AI-enabled mobile app for maternal and child health care in Cambodia - a pilot implementation and evaluation study
OBJECTIVES: In Cambodia, village health support groups (VHSGs) are central to maternal and child health (MCH) service delivery, yet maternal mortality remains high with regional disparities. Although digital health solutions show promise, their real-world use is underexplored. This study therefore aims to evaluate the i-MoMCARE app in supporting VHSGs and health centre staff for delivering MCH services. METHODS: A mixed-methods approach guided by the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework was used. Reach was assessed using programme records (number of users trained and MCH cases managed). Effectiveness and adoption were evaluated using the mHealth App Usability Questionnaire (MAUQ) and qualitative data on user experience and intention to use. Implementation was examined through system usage monitoring and feedback on workflow integration. Maintenance was explored using qualitative insights on long-term use, barriers and recommendations. RESULTS: 44 VHSGs and 10 health centre staff were trained, and 96 MCH cases were managed with the app. Usefulness was rated highly (MAUQ 5.58, SD 1.04), with users appreciating the user-centric design that improved usability and integration into daily workflows. Effectiveness was similarly high (MAUQ 5.50, SD 0.95); the clinical decision support system and point-of-care alerts were valued as reliable decision-support tools, and the electronic medical record (EMR) was seen as a secure data repository. However, adoption was hindered by hardware and software limitations (MAUQ 5.79, SD 0.75), including device availability and low digital literacy. DISCUSSION: Our findings highlight the value of the i-MoMCARE app in supporting VHSGs, particularly those with limited training, by enhancing their decision-making. The study also lays the groundwork for a unified EMR in primary care. However, concerns around hardware and software limitations hinder adoption and sustained use. CONCLUSION: To enable scale-up, we recommend reducing access barriers and supporting sustained use through diversifying the platform's design and implementing phased incentivisation strategies.
27 Apr 2026
Read appraisal →BMJ open
Do studies of interventions to improve laypeople's critical thinking about health choices assess potential harms? A systematic review.
OBJECTIVES: To make informed health choices, and avoid waste and unnecessary suffering, people need critical thinking skills. However, like health interventions, educational interventions can have adverse effects. In this systematic review, the objective was to assess the extent to which researchers have included potential adverse effects in studies of interventions intended to improve the critical thinking of laypeople about health choices. DESIGN: This study was a systematic review, in which we updated the search for an earlier systematic review of intended effects of relevant interventions. The earlier review did not address potential adverse effects. We did not update the analysis of intended effects. DATA SOURCES: We searched Cochrane Central Register of Controlled Trials (CENTRAL), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, Epistemonikos, Medical Literature Analysis and Retrieval System Online (MEDLINE), Education Resources Information Center (ERIC) and Web of Science up to March 2025. In addition to studies from the original review and updated search, we included any additional studies included in a similar, even earlier review. Our unit of analysis was study report (eg, journal article). ELIGIBILITY CRITERIA: We included all studies from the original review. We applied the same inclusion criteria to the results of the updated search: the study included a comparison, the population was laypeople and the intervention was intended to improve understanding of ≥1 key concept for informed health choices. DATA EXTRACTION AND SYNTHESIS: We extracted data about study design (randomised trial or other), participants (children, adolescents or adults), study setting (countries), main intervention (resources delivered to participants) and comparator (usual/no intervention or other). For the analysis, we extracted verbatim text describing any assessment of a potential adverse effect of the intervention. We conducted a narrative synthesis of the extracted data. RESULTS: We included 35 reports of quantitative studies (including multi-method and mixed-methods studies). Most often, the study was a randomised trial, the setting was a high-income country, the population included adults (including university students) and the intervention was school-based (including university). In one of the 35 reports, authors described assessing a potential adverse effect. CONCLUSION: To our knowledge, this is the first systematic review assessing the extent to which researchers have assessed adverse effects of any category of educational interventions. Our review shows that researchers generally have not assessed potential adverse effects of interventions to improve critical thinking about health choices. Researchers should pay more attention to such effects, while policymakers and educators making decisions about implementing relevant interventions should consider the lack of evidence. The findings of this study suggest a need for research that facilitates assessing potential adverse effects of interventions to improve critical thinking about health choices.
27 Apr 2026
Read appraisal →BMJ paediatrics open
Metabolically obese normal weight phenotype in children and adolescents aged 3 to 18 years: a systematic review
BACKGROUND: Children with normal Body Mass Index (BMI) may still exhibit adverse metabolic profile-termed as the metabolically obese normal weight (MONW) phenotype, placing them at increased risk of long-term cardiometabolic complications. OBJECTIVE: To systematically synthesise the evidence of the MONW phenotype in children and adolescents aged 3-18 years, and to identify early-life determinants. METHODS: This systematic review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines and searched PubMed/ MEDical Literature Analysis and Retrieval System On-Line (MEDLINE), Scopus, Web of Science (WoS), Google Scholar, Embase and Cochrane Library for studies from 2000 to January 2026. Observational studies of children and adolescents aged 3-18 years with normal BMI and at least one metabolic abnormality were included. Two reviewers independently screened the studies, extracted data and assessed risk of bias. Searches were conducted between March 2025 and January 2026, and 11 studies met the predefined inclusion and exclusion criteria. RESULTS: The reported prevalence of MONW ranged from 10.6% to 56.2%, varying by diagnostic criteria and population. Children with MONW consistently showed higher visceral adiposity, insulin resistance (IR), dyslipidaemia, hypertension, impaired glucose metabolism and elevated markers of low-grade inflammation despite having normal BMI. Early-life determinants included extremes of birth weight, rapid infant weight gain, adverse maternal metabolic status, unhealthy dietary patterns and sedentary behaviour. Overall risk of bias across studies was judged to be low to moderate, with the main concerns relating to residual confounding and use of heterogeneous MONW definitions. CONCLUSIONS: MONW represents a clinically relevant but under-recognised paediatric phenotype. Reliance on BMI alone may delay identification of vulnerable children. Early risk stratification integrating metabolic proofing and central adiposity measures may enable timely prevention of long-term metabolic disease. Harmonised operational definitions of MONW and robust longitudinal life-course studies are required to inform evidence-based screening thresholds and preventive interventions.
27 Apr 2026
Read appraisal →JAAPA : official journal of the American Academy of Physician Assistants
Barriers to hearing aid adoption in hearing loss
More than one-fifth of the US population has hearing loss, a condition associated with higher risk of falls, depression, isolation, cognitive decline, dementia, and all-cause mortality. Treatment of hearing loss has been shown to correlate with decreased risk of cognitive decline, dementia, and mortality, as well as an improved quality of life. Surprisingly, however, fewer than 1 in 10 Americans with hearing loss use hearing aids. As the prevalence and burden of hearing loss grow, clinicians must understand factors influencing hearing aid use to increase treatment rates. This article reviews key barriers to hearing aid adoption-including low hearing health knowledge, inadequate screening, stigma, cost, and difficulty of use-and discusses recent changes that may influence these barriers.
27 Apr 2026
Read appraisal →PloS one
The stress reduction potential of Bhagavad Gita and Yoga for healthcare workers during the COVID-19 pandemic: A randomized controlled trial
BACKGROUND: Healthcare workers (HCWs) experienced elevated psychological distress during the COVID-19 pandemic. Culturally embedded, non-stigmatizing approaches may improve uptake of mental health support in this population. We aimed to evaluate the impact of Yoga, Bhagavad Gita learning, and their combination (Yoga+Gita) on psychological distress among HCWs. METHODS: We conducted a prospective, single-center, parallel-group randomized controlled trial at a secondary hospital in India. Eligible HCWs (>18 years, without pre-existing diagnosed mental health conditions) were randomized in a 1:1:1:1 ratio to: Yoga (daily 60-min sessions for one week), Gita (daily 60-min teaching of Bhagavad Gita Chapter 2 for one week), Yoga+Gita (30 min Yoga + 30 min Gita daily for one week), or Control (usual care). Psychological distress was assessed using the Generalized Anxiety Disorder-7 (GAD7) scale at baseline (B-GAD7), immediately post-intervention (IPI-GAD7), and 45 days post-intervention (DPI-GAD7). Participants were aware of group assignment, but data analysts were blinded. Group comparisons used Friedman and Kruskal-Wallis tests with Bonferroni-adjusted post-hoc analyses. We hypothesized that (1) all three interventions would reduce GAD-7 scores compared with control, (2) Gita would produce more durable effects than Yoga alone, and (3) the combined Yoga+Gita intervention would yield the greatest overall reduction in psychological distress. FINDINGS: Sixty-eight participants were enrolled (17 per group), with no losses to follow-up. B-GAD7 did not differ across groups (p = 0.908). Compared with Control, Yoga+Gita reduced anxiety immediately (p = 0.009), and Gita reduced anxiety at 45 days (p = 0.047). A clinically meaningful (≥4-point) GAD7 reduction at 45 days occurred in 17.6% (Yoga), 47.1% (Gita), 41.2% (Yoga+Gita), and 11.8% (Control) of the participants. Exploratory analyses suggested larger benefits among women and among those who continued practice. INTERPRETATION: Yoga and Gita-learning, particularly in combination, were associated with reductions in psychological distress among HCWs. TRIAL REGISTRATION: Prospectively registered with the CTRI (CTRI/2021/10/037365).
27 Apr 2026
Read appraisal →PloS one
Protocol for a randomized pilot trial of COMPASS, an open‑source, culturally adapted cognitive behavioral therapy program for forcibly displaced Venezuelan adults in Peru
Task-sharing approaches have shown promise in low-resource settings, yet few culturally adapted interventions have been systematically evaluated for forcibly displaced populations. Since 2016, over 1.7 million Venezuelans have migrated to Peru, facing significant barriers to healthcare and elevated risks of anxiety, depression, and post-traumatic stress disorder (PTSD). This protocol describes COMPASS (Cognitive-behavioral Open-source Mental-health Program Adapted for migrants, Sustainably delivered by lay providers and Supported by evidence). COMPASS is a transdiagnostic, open-source cognitive behavioral therapy program co-designed with forcibly displaced populations. This protocol describes the procedures for an ongoing randomized pilot trial with n = 90 forcibly displaced Venezuelan people (Clinicaltrials.gov: NCT06635486). COMPASS guides, or lay providers, trained through an intensive apprenticeship model, will deliver 6-12 weekly remote sessions. Primary outcomes include changes in anxiety, depression, and PTSD symptoms, assessed with validated Spanish-language measures. Secondary outcomes include feasibility (recruitment, retention, fidelity) and acceptability (therapist and participant ratings). Exploratory outcomes will examine integration, migration experiences, and demographic moderators of intervention effectiveness. Analyses will follow the intention-to-treat principle, using descriptive statistics and regression models to evaluate symptom trajectories across baseline, post-intervention, and 3- and 6-month follow-ups. This study represents the first effectiveness evaluation of an open-source, lay-delivered CBT program tailored for forcibly displaced people in Peru. Findings will inform feasibility, acceptability, and preliminary effectiveness of COMPASS, with potential to expand scalable, culturally relevant mental health services for forcibly displaced populations in resource-constrained settings worldwide.
27 Apr 2026
Read appraisal →PloS one
Disparity of ophthalmic surgeries in Japan
PURPOSE: Although regional disparities in access to surgical care have been reported across medical specialties, nationwide evaluations of variation in ophthalmic surgical services remain limited. This study examined prefecture-level differences in major ophthalmic surgeries in Japan using publicly available claims data. METHODS: We analyzed the ninth release of the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB Open Data) for fiscal year 2022 (April 2022-March 2023). Prefecture-level procedure counts were extracted for cataract surgery (K282), vitrectomy (K279-K281 and related codes), glaucoma surgery (relevant K-codes), and corneal transplantation. To reduce potential underestimation in non-Diagnosis Procedure Combination settings, ophthalmology-related procedures reimbursed under the Short-Stay Surgery Basic Fee 3 (A400) were identified and incorporated according to predefined mapping rules. Surgical rates per 100,000 population and per board-certified ophthalmologist were calculated. Regional inequality was quantified using population-weighted Gini coefficients. Associations between ophthalmologist density and surgical volume were assessed using Pearson's correlation coefficients. RESULTS: Nationwide totals were 1,777,502 cataract surgeries, 154,336 vitrectomies, 80,753 glaucoma surgeries, and 2,895 corneal transplantations. Prefecture-level surgical rates per 100,000 population varied 1.8-fold for cataract surgery, 3.3-fold for vitrectomy, and 7.8-fold for glaucoma surgery. Several prefectures reported no corneal transplantation cases. Population-weighted Gini coefficients were 0.064 for cataract surgery, 0.125 for vitrectomy, 0.190 for glaucoma surgery, and 0.351 for corneal transplantation. Similar patterns were observed after adjusting for age structure, indicating that regional disparities were not solely explained by demographic differences. Ophthalmologist density varied 2.5-fold across prefectures and was positively correlated with surgical volume for cataract surgery and vitrectomy, but not for glaucoma surgery. CONCLUSIONS: Using nationwide claims data, we identified substantial regional variation in major ophthalmic surgical procedures in Japan, with greater inequality observed for more specialized surgeries. These findings provide a population-level description of ophthalmic surgical distribution and may inform future evaluations of healthcare resource allocation.
27 Apr 2026
Read appraisal →American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Tech That Scales: A Practical Framework for Artificial Intelligence-Enabled Cancer Care in Low- and Middle-Income Countries and Underserved US Counties
Cancer outcomes remain starkly unequal: 5-year survival rates for common malignancies in low- and middle-income countries (LMICs) often lag 20-40 percentage points behind high-income benchmarks, and similar disparities persist between well-resourced metropolitan centers and rural or safety-net settings within high-income countries. The gap is driven less by the absence of effective interventions than by workforce shortages, fragmented referral pathways, limited infrastructure, and loss to follow-up after abnormal screens. Technologies that scale must therefore function as deployable workflows integrating staffing, logistics, quality assurance (QA), governance, and monitoring not merely as stand-alone algorithms or devices.1 This review synthesizes evidence across four complementary technology families that address these constraints across the continuum of care: artificial intelligence (AI)-supported screening and triage as the population entry-point layer; Project ECHO telementoring as the workforce-capacity layer; electronic patient-reported outcomes and remote symptom monitoring as the longitudinal continuity layer; and AI-powered clinical trial prescreening hubs as the access-to-innovation layer. The technologies do not carry equal evidentiary weight, and they should not be deployed identically in every setting. Our aim is to show how oncology leaders can sequence them pragmatically inside a common operating logic while adapting to local infrastructure and governance. We organize the framework in patient journey order entry into care through screening, workforce support through telementoring, continuity through remote monitoring, and access to innovation through trial prescreening, and draw examples from both LMIC programs and underserved US settings. We therefore present a practical implementation playbook, including a 90-day launch checklist, staffing models, QA frameworks, equity and bias monitoring metrics, and a program outcomes dashboard designed for oncology leaders seeking to move beyond pilots toward durable, monitored deployment.
27 Apr 2026
Read appraisal →PloS one
Machine learning identifies pupil size and corneal thickness as key predictors of axial elongation rate
PURPOSE: This study aimed to develop a machine learning-based prediction model for myopia progression using ocular biometric parameters to provide an objective assessment tool for clinical practice. METHODS: A retrospective analysis was conducted on patients treated at Shanghai Parkway Health Ophthalmology Department as the training set, and myopic individuals from the Optometry Center of Peking University People's Hospital as the validation set. Demographic and biometric data were collected, including central corneal thickness (CCT), axial length (AL), corneal curvature (K-value), anterior chamber depth (ACD), corneal diameter (WTW), and pupil size (PS). Seven machine learning models (e.g., XGBoost, random forest, support vector machine) were employed for modeling, with performance optimized via 5-fold cross-validation. Model accuracy was evaluated using mean squared error (MSE) and the coefficient of determination (R²), and variable importance was analyzed. RESULTS: No statistically significant differences were observed in baseline characteristics between the training and validation sets (all P > 0.05). The XGBoost model demonstrated the best performance, achieving R² = 0.913 (MSE = 0.005) on the training set and R² = 0.766 (MSE = 0.016) on the test set. Variable importance analysis revealed pupil size (score 100) and corneal thickness (40.88) as the key predictors of axial elongation rate, followed by age of onset (17.96). CONCLUSION: The machine learning-based prediction model effectively utilizes ocular biometric data to assess myopia progression risk, with pupil size and corneal thickness identified as core predictive factors. This model provides a quantitative tool for early clinical intervention. Future studies should expand the sample size and incorporate additional biomarkers to optimize performance.
27 Apr 2026
Read appraisal →Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology
Antenatal psychological interventions may ameliorate postpartum depression: a systematic review and meta-analysis
BACKGROUND: This study aimed to systematically evaluate the effects of psychological interventions during pregnancy on the intervention outcomes and incidence rate in women with postpartum depression. METHODS: Databases (PubMed, Medline, Web of Science, Cochrane Library, EMBASE) were searched from inception to December 2024 for randomised controlled trials assessing prenatal psychological interventions (e.g., mindfulness, psychosocial support) in pregnant women without severe mental illness. Primary outcomes included Edinburgh Postnatal Depression Scale (EPDS), Patient Health Questionnaire-9 (PHQ-9), Perceived Stress Scale-10 (PSS-10), Spielberger State-Trait Anxiety Inventory (STAI) scores, and PPD incidence within 6 weeks postpartum. Quality was assessed using the Cochrane risk-of-bias tool; meta-analysis was performed with RevMan 5.3. RESULTS: A total of 10 articles were included, with 6700 study subjects in total, including 3345 in the intervention group and 3355 in the control group, all of which were randomised controlled trials. The incidence rate of postpartum depression in the intervention group was significantly reduced (OR = 0.73, 95% CI [0.57-0.95], P = 0.02). The scores of EPDS, PHQ-9, PSS-10, and STAI in the intervention group were all lower than those in the control group. CONCLUSION: Psychological interventions during pregnancy can significantly reduce postpartum depression-related scale scores and incidence rates, and improve depressive symptoms, anxiety, and perceived stress. However, due to the heterogeneity of intervention types, this study cannot determine the optimal intervention method and thus provides preliminary evidence for clinical prevention. Clinicians should select interventions based on resource availability and individual characteristics of pregnant women, while future studies should focus on direct comparisons of different intervention types to provide more targeted guidance. Postpartum depression is a common mental health problem that affects many women after childbirth. It can harm both the mother’s well-being and the baby’s development. This study combined data from ten clinical trials, including 6,700 participants, to evaluate whether psychological interventions during pregnancy can help prevent postpartum depression. The results showed that women who received psychological support—such as mindfulness training, counselling, or group therapy—had fewer depressive symptoms, lower anxiety and stress levels, and a significantly reduced incidence rate compared with those who received routine care. These findings suggest that providing psychological care during pregnancy is an effective way to reduce the risk of postpartum depression and to promote mental health for both mothers and infants. Early psychological support should be considered an important part of prenatal care.
26 Apr 2026
Read appraisal →ACS sensors
All-in-One Wearable Hydrogel Patch for Multimodal Visualized and Quantitative Heatstroke Monitoring
Heat-related illnesses, particularly heatstroke, pose serious risks to outdoor workers, athletes, and individuals with impaired thermoregulation. Existing monitoring strategies are limited by invasive measurements, reliance on external power sources, and lack of real-time multimodal feedback. Here, this study presents an all-in-one wearable patch that integrates a dual-functional self-powered thermogalvanic hydrogel with a selective electrochemical interface for intuitive visual feedback, dynamic temperature tracking, and durable sweat analysis. The hydrogel enables real-time thermochromic visualization and active thermoelectric sensing of body temperature, while an integrated electrochemical module allows continuous and selective detection of Na+ and K+ ions in sweat. The multiplexed physical-chemical health-monitoring patch provides a multimodal dual-stage evaluation of body temperature and sweat ion level toward improving metabolic status control and alerting individual to heatstroke risk, holding promise for developing personalized healthcare and a scalable route to proactive heatstroke prevention.
26 Apr 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
ACT on Vaping: Pilot Randomized Controlled Trial of a Novel Digital Health App With Text Messaging for Young Adult Vaping Cessation
BACKGROUND: There is no published evidence to support the efficacy of any digital vaping cessation program for young adults (YAs) at differing levels of readiness to quit. In this pilot randomized controlled trial, we evaluated the preliminary acceptability and efficacy of a program for vaping cessation based on acceptance and commitment therapy (ACT on Vaping), delivered via a smartphone app and text messaging. METHODS: YAs aged 18-30 (n = 61) were randomized 1:1 to ACT on Vaping (n = 31) or incentivized text message control (n = 30). Outcome data were collected at 3 months post-randomization. Results were compared against a priori benchmarks for acceptability (satisfaction of ≥3.5 on 5-point scale) and efficacy relative to control (meeting at least one of three): ≥1-point difference in Contemplation Ladder change scores; ≥5 percentage difference in 24-hour quit attempts, ≥5 percentage difference in cotinine-confirmed 30-day point prevalence abstinence (PPA) from all non-therapeutic nicotine/tobacco. RESULTS: Satisfaction with ACT on Vaping averaged 3.8, exceeding the acceptability benchmark. A higher proportion of participants in the ACT on Vaping arm reported a 24-hour quit attempt (87.5% vs. 75.9%), exceeding the efficacy benchmark. Both changes in quit readiness (+0.96 in ACT on Vaping vs. +0.72 in control) and cotinine-confirmed 30-day PPA (4.2% in ACT on Vaping vs. 0% in control) were descriptively higher for ACT on Vaping but did not reach the benchmark level for efficacy. CONCLUSIONS: ACT on Vaping had promising acceptability and preliminary efficacy. A fully powered trial of ACT on Vaping is warranted to evaluate its efficacy. IMPLICATIONS: Digital interventions are a promising yet under-researched approach for reaching and supporting YAs to quit vaping. This proof-of-concept pilot randomized controlled trial evaluated a novel mobile health application and associated text messaging program (ACT on Vaping) for young adult vaping cessation and found preliminary evidence for acceptability and efficacy relative to an incentivized text message control arm, warranting evaluation in a fully powered trial as a next step. TRIAL REGISTRATION: NCT05897242.
26 Apr 2026
Read appraisal →JMIR mental health
Effectiveness of a Fully Automated Mobile Therapeutic Versus a General Chatbot in Reducing Depression and Anxiety and Improving Well-Being: Feasibility Randomized Controlled Trial
BACKGROUND: Given the increasing prevalence of depression and anxiety disorders and enduring barriers to care, there is a critical need for alternative treatment options. Generative artificial intelligence (AI) chatbots show promise for increasing access to mental health care, though more direct research is needed to establish their efficacy. OBJECTIVE: This pilot study aimed to test the efficacy of a generative mental health chatbot rooted in solution-focused therapy compared to the general-purpose ChatGPT and an assessment-only control (AOC) group on depression, anxiety, and well-being. METHODS: A total of 185 English-speaking adults were recruited online and randomly assigned to one of three groups: AI therapy, ChatGPT, or AOC. Of these, 147 eligible participants filled out a pretreatment assessment. Over a 3-week period, the AI therapy group (n=44) was instructed to complete 3 structured, fully automated app-based sessions per week (9 total), while the ChatGPT group (n=60) was instructed to engage in 9 unstructured conversations with ChatGPT (GPT-4o-based models). The control group (n=43) received no intervention. In the AI therapy group, 39% (n=17) completed all sessions, as did 62% (n=38) of those in the ChatGPT group. Primary outcome measures, self-assessed online at baseline and postintervention, included the Patient Health Questionnaire-9 (PHQ-9), Overall Depression Severity and Impairment Scale (ODSIS) (depression), 7-item Generalized Anxiety Disorder Scale (anxiety), and World Health Organization Well-Being Index (5-item version) (well-being). Linear mixed effects models were used for data analysis. RESULTS: Compared to AOC, both the AI therapy group (d=-0.47; P=.01) and the ChatGPT group (d=-0.44; P=.02) demonstrated significant reductions in depression scores measured by PHQ-9. The AI therapy group showed nonsignificant reductions in anxiety (d=-0.37; P=.11) and ODSIS depression scores (d=-0.25; P=.22) and an increase in well-being (d=0.12; P=.53) compared to AOC. Similarly, a nonsignificant reduction in anxiety (d=-0.27; P=.22) and ODSIS depression scores (d=-0.12; P=.53) and an increase in well-being (d=0.20; P=.29) were observed in the ChatGPT group compared to AOC. The AI therapy group did not significantly outperform the ChatGPT group on any outcomes (PHQ-9: b=-0.19; d=0.03; P=.87; 7-item Generalized Anxiety Disorder Scale: b=-0.57; d=-0.11; P=.62; ODSIS: b=-0.59; d=-0.13; P=.50; and WHO: b=-0.38; d=-0.07; P=.69). CONCLUSIONS: Both the structured generative AI chatbot and ChatGPT showed a significant reduction in depression scores compared to the control group. No significant effects were observed across other outcomes, although descriptive trends indicated improvements in anxiety. While the AI therapy group showed descriptively better outcomes for depression and anxiety, differences between groups were not significant. A larger sample and longer intervention may be needed for the emerging trends to yield clinically meaningful effect sizes.
26 Apr 2026
Read appraisal →Proceedings of the National Academy of Sciences of the United States of America
Cumulative access to print books improves literacy achievement: Evidence from a five-year randomized trial in high-poverty schools
For more than a century, studies have shown that children who grow up in homes with more books achieve higher levels of academic success, yet it remains unclear whether books themselves improve learning or simply reflect broader socioeconomic advantages. Skill-development theory holds that greater access to books directly improves literacy through increased print exposure and reading practice, whereas the cultural capital account suggests books are indicators of broader family resources, including parental education, academic norms, and enrichment opportunities, that promote achievement independently of the books themselves. To provide causal evidence, we conducted a school-level randomized controlled trial of a program that builds children's home libraries. In 2018, we randomly assigned 60 high-poverty public elementary schools to treatment or control groups. Students in 30 treatment schools received four book distributions over 5 y, averaging about seven books per distribution, and prominently including high-interest and culturally relevant titles; students in 30 control schools received none. Tracking students from 2018-19 through 2022-23, we find a statistically significant intention-to-treat impact on reading achievement of d = 0.100 and a larger d = 0.207 advantage for those completing the full 5-y program. These impacts correspond to approximately 25 to 32% and 52 to 65% of a typical year's learning, respectively. The largest benefits are concentrated among students who received books across all distributions, indicating that cumulative exposure drives the strongest impacts. These findings provide evidence supporting skill-development theory and highlight a scalable strategy for improving literacy outcomes in high-poverty urban schools.
26 Apr 2026
Read appraisal →Biomedizinische Technik. Biomedical engineering
AI in healthcare: mapping Romania's transition from research to intellectual property & industry solutions
OBJECTIVES: Romania is aligning its healthcare AI ecosystem with the European Union's AI Act (2024/1689), through its own National AI Strategy. Despite a growing volume of research in medical AI, significant gaps remain in translating this output into patents and domestically developed high-risk medical devices. This study assesses Romania's research productivity, patenting activity, and commercial solutions in medical AI. METHODS: We conducted an analysis combining bibliometric data, patent information, and medical device databases, and analyzed 619 Romanian-authored articles on medical AI, 272 patent records, and identified domestic AI-powered software providers. RESULTS: Romania's publication output in medical AI has surged post-2018, primarily driven by academic institutions in Bucharest and Cluj. Patents are predominantly filed by multinationals, indicating a potential disconnect between research and industrial output. Six AI medical software solutions were identified, most under the low-risk classifications. CONCLUSIONS: While Romania is expanding its medical AI research, it faces barriers in converting academic output into innovation. The dominance of foreign corporations in patent filings, reliance on international funding for high-impact research, and the scarcity of domestically developed high-risk medical AI solutions highlight important gaps. Addressing these disparities is essential for national alignment in the AI medical innovation space.
26 Apr 2026
Read appraisal →The British journal of ophthalmology
Ethnic and dose-dependent differences in atropine efficacy for myopia control: a systematic review and meta-analysis
BACKGROUND/AIM: Clinical uncertainty remains regarding optimal atropine concentration, treatment duration and potential differences in efficacy for myopia control between Asian and non-Asian children. This systematic review and meta-analysis evaluated the efficacy of different concentrations of atropine for myopia control, comparing outcomes among East Asian, South Asian and white European children. METHODS: Five databases were searched for randomised controlled trials (RCTs) including children ≤16 years with myopia who received atropine treatment. Thirty-four RCTs with ≥12 months of follow-up were included. Weighted mean differences (WMD) in spherical equivalent refraction (SER) progression and axial length (AL) elongation were pooled by atropine concentration and ethnicity. RESULTS: Compared with controls, atropine significantly reduced myopia progression across all concentrations: <0.1% (WMD in SER: 0.44 (95% CI 0.35 to 0.52) dioptres (D)/year; AL: -0.20 (95% CI -0.24 to -0.16) mm/year), 0.1% to <0.5% (0.81 (95% CI 0.50 to 1.13) D/year) and ≥0.5% (1.06 (95% CI 0.88 to 1.24) D/year; -0.36 (95% CI -0.40 to -0.33) mm/year). The pooled effect on SER and AL progression across all concentrations was greater in East Asians (0.63 (95% CI 0.50 to 0.76) D/year; -0.26 (95% CI -0.31 to -0.20) mm/year) than in South Asians (0.40 (95% CI 0.11 to 0.70) D/year; -0.13 (95% CI -0.21 to -0.05) mm/year) or white Europeans (0.18 (95% CI 0.11 to 0.25) D/year; -0.11 (95% CI -0.16 to -0.05) mm/year). CONCLUSION: Atropine slows myopia progression in a dose-dependent manner in studies with 1-5 years of follow-up. Efficacy appears greater in Asian children, particularly East Asians, who also exhibit greater photopic pupil dilation. These findings support the role of atropine in myopia control and highlight the importance of ethnicity-specific considerations when prescribing and tailoring treatment strategies. PROSPERO REGISTRATION NUMBER: CRD42023454104.
26 Apr 2026
Read appraisal →JMIR aging
The Associations Between Digital Exclusion and Physical or Cognitive Function in Middle-Aged and Older Adults: Systematic Review and Meta-Analysis
BACKGROUND: Digital exclusion posed a significant challenge, especially in middle-aged and older adults, which affected their health outcomes. However, the evidence regarding the associations of digital exclusion on physical or cognitive function outcomes was controversial, and no systematic review had been performed to synthesize the pooled associations. OBJECTIVE: This study aimed to explore the relationship between digital exclusion and physical or cognitive function in middle-aged and older adults. METHODS: We conducted a systematic review and meta-analysis of cohort and cross-sectional studies, including Chinese or English publications retrieved from PubMed, Embase, Web of Science, PsycINFO, Scopus, CNKI, and Wanfang databases up to August 31, 2024. The risk of bias was evaluated using the Newcastle-Ottawa Scale (NOS). The pooled effect size was calculated based on odds ratios (ORs), hazard ratios, risk ratios, and 95% CIs. This study was registered on PROSPERO (CRD42024585459). RESULTS: Nineteen studies met the inclusion criteria, including 13 cohort studies and 6 cross-sectional studies, which had moderate-to-low risk of bias. The pooled analysis indicated that digital exclusion had prospective associations with decreased basic activities of daily living (incidence rate ratio 1.35, 95% CI 1.12-1.64, I2=94.7%) and instrumental activities of daily living (incidence rate ratio 1.46, 95% CI 1.13-1.89, I2=96.2%), or cross-sectional association with activities of daily living (OR 1.23, 95% CI 0.41-3.73, I2=91%), with no statistical significance in the prospective association with frailty (OR 1.21, 95% CI 0.92-1.59, I2=95.2%). There were prospective associations between digital exclusion and dementia (hazard ratio 1.78, 95% CI 1.43-2.22, I2=0%), decreased Mini-Mental State Examination scores (OR 1.96, 95% CI 1.39-2.75, I2=0%), as well as cross-sectional associations with Mini-Mental State Examination scores (OR 2.90, 95% CI 2.07-4.07, I2=0%), and no statistical significance in the prospective association with cognitive impairment (risk ratio 2.08, 95% CI 0.98-4.44, I2=78.2%). CONCLUSIONS: Our findings indicated the negative associations of digital exclusion with physical and cognitive functions. Future research and clinical practice should consider designing digital interventions and services that match the physical and cognitive capacities and preferences of middle-aged and older adults, thereby improving digital engagement and reducing the harms associated with digital exclusion. Policies should focus on expanding access, reducing financial barriers, and improving digital literacy. However, due to the presence of heterogeneity and publication bias, the results should be interpreted cautiously.
26 Apr 2026
Read appraisal →BMJ open
Effects of nurse-led shared decision-making on low-dose CT uptake and screening outcomes in high-risk populations: a systematic review and meta-analysis
OBJECTIVES: To evaluate the effects of nurse-led shared decision-making (SDM) on lung cancer screening outcomes, including low-dose CT (LDCT) uptake, benign findings, early cancer detection and willingness to participate among high-risk populations. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed, Medline via OvidSP, Cochrane Central Register of Controlled Trials, EMBASE via OvidSP, Web of Science, Scopus, grey literature databases and clinical trial registries were searched from inception to March 2025. ELIGIBILITY CRITERIA: Studies evaluating nurse-led SDM interventions in high-risk lung cancer populations, reporting outcomes including LDCT uptake rates, screening results (Lung-RADS (Lung Imaging Reporting and Data System) classifications), early-stage cancer detection or willingness to participate. Randomised controlled trials, quasi-experimental studies and observational studies were included. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently extracted data and assessed risk of bias using the Risk of Bias in Non-randomised Studies of Interventions (for non-randomised studies) and Cochrane Risk of Bias 2.0 (for randomised controlled trials). Meta-analyses were conducted using random-effects models. Meta-regression explored sources of heterogeneity. RESULTS: 13 studies (n=13 608 participants) were included, comprising 10 single-arm studies and three comparative studies. In single-arm studies without control groups, nurse-led SDM programmes achieved a pooled LDCT uptake rate of 98% (95% CI 28% to 100%; I²=99%), and willingness to participate was 68% (95% CI 24% to 93%; I²=98%). In comparative studies, nurse-led SDM showed no significant difference in LDCT uptake compared with usual care (RR 1.00, 95% CI 0.99 to 1.02; I²=0%), suggesting non-inferiority rather than superiority. Among individuals who completed screening, 81% (95% CI 77% to 85%) had benign or low-risk findings (Lung-RADS [Lung Imaging Reporting and Data System] I/II), and 2% (95% CI 1% to 3%) were diagnosed with early-stage lung cancer, rates consistent with benchmark screening trials. Meta-regression identified female sex as positively associated with uptake (β=0.54, p<0.001), while current tobacco use was negatively associated (β=-0.37, p=0.033). The risk of bias was moderate to serious across studies. CONCLUSIONS: Comparative evidence suggests that nurse-led SDM achieves equivalent LDCT uptake to standard care approaches, indicating feasibility as an alternative service delivery model. However, the predominance of single-arm studies, high heterogeneity and moderate-to-serious risk of bias limit causal inference. High uptake rates in single-arm studies likely reflect selection bias rather than intervention effectiveness. Current evidence supports the feasibility but not the superiority of nurse-led SDM. Well-designed randomised controlled trials are needed to establish comparative effectiveness and cost-effectiveness before recommending widespread integration of nurse-led SDM into lung cancer screening programmes. TRIAL REGISTRATION NUMBER: PROSPERO CRD420251033595. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=1033595.
26 Apr 2026
Read appraisal →The New England journal of medicine
Oral Nirmatrelvir-Ritonavir for Covid-19 in Higher-Risk Outpatients
BACKGROUND: Nirmatrelvir-ritonavir has been shown to reduce progression to severe illness from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in unvaccinated high-risk outpatients. The effectiveness of nirmatrelvir-ritonavir in persons who have been vaccinated, infected naturally, or both is unclear. METHODS: In two open-label platform trials (PANORAMIC in the United Kingdom and CanTreatCOVID in Canada), we enrolled higher-risk adults (≥50 years of age or ≥18 years of age with coexisting conditions) in the community who tested positive for SARS-CoV-2 and had been unwell for 5 days or less. The participants were randomly assigned to receive usual care plus nirmatrelvir (300 mg)-ritonavir (100 mg) twice a day for 5 days or to receive usual care alone. The primary outcome was hospitalization or death from any cause within 28 days after randomization. RESULTS: From December 8, 2021, to September 30, 2024, a total of 3516 participants in the PANORAMIC trial and 716 participants in the CanTreatCOVID trial underwent randomization. In the PANORAMIC trial, 14 of 1698 participants (0.8%) in the nirmatrelvir-ritonavir group and 11 of 1673 participants (0.7%) in the usual-care group were hospitalized or died (adjusted odds ratio, 1.18; 95% Bayesian credible interval, 0.55 to 2.62; probability of superiority, 0.334). In the CanTreatCOVID trial, 2 of 343 participants (0.6%) in the nirmatrelvir-ritonavir group and 4 of 324 participants (1.2%) in the usual-care group were hospitalized or died (adjusted odds ratio, 0.48; 95% Bayesian credible interval, 0.08 to 2.23; probability of superiority, 0.830). In a substudy involving 634 participants, viral load was reduced by the end of treatment with nirmatrelvir-ritonavir. Serious adverse events with nirmatrelvir-ritonavir were reported in 9 participants in the PANORAMIC trial and in 4 participants in the CanTreatCOVID trial. CONCLUSIONS: In two open-label trials, nirmatrelvir-ritonavir did not reduce the incidence of hospitalization or death among vaccinated higher-risk participants with SARS-CoV-2 infection. (Funded by the National Institute for Health and Care Research, and others; PANORAMIC ISRCTN number, 2021-005748-31; CanTreatCOVID ClinicalTrials.gov number, NCT05614349.).
25 Apr 2026
Read appraisal →Journal of medical Internet research
Personalized Smartphone Messaging for Secondary Prevention After Percutaneous Coronary Intervention: Randomized Controlled Trial
BACKGROUND: Cardiac rehabilitation improves outcomes after percutaneous coronary intervention (PCI), but participation remains suboptimal due to barriers such as distance, cost, and lack of referral. Mobile health interventions may enhance accessibility and engagement. OBJECTIVE: This study evaluated the effectiveness and user acceptability of a smartphone messaging app (AnSim) in improving cardiovascular risk factors among patients who recently underwent PCI. METHODS: A 2-arm randomized controlled trial was conducted at 2 Korean hospitals; 120 patients who had undergone PCI within the prior month were randomized (1:1) to receive AnSim plus usual care (intervention) or usual care alone (control). The intervention comprised personalized messages tailored by behavioral stage and risk profile, delivered 6 times/week for 6 months. Outcomes were assessed at baseline, 6 months, and 9 months. The primary outcome was change in blood pressure (BP) at 6 and 9 months. Secondary outcomes were lipid profiles, hemoglobin A1c, BMI, smoking status, physical activity, and achievement of guideline-recommended risk-factor targets. User acceptability was assessed by questionnaire. RESULTS: Overall, 115 (95.8%; intervention: n=58, control: n=57) participants completed follow-up at 6 months and 110 (91.7%; intervention: n=54, control: n=56) at 9 months. At 6 months, systolic BP was 124.9 (SD 16.7) mmHg in the intervention group and 124.8 (SD 13.1) mmHg in the control group (between-group difference 0.1 mmHg, 95% CI -5.4 to 5.6), and diastolic BP was 80.2 (SD 11.4) mmHg vs 78.4 (SD 10.6) mmHg (difference 1.8 mmHg, 95% CI -2.3 to 5.9). At 9 months, systolic BP was 126 (SD 14.2) mmHg vs 128 (SD 15.4) mmHg (difference -2 mmHg, 95% CI -7.6 to 3.6), and diastolic BP was 80.8 (SD 13.2) mmHg vs 81.3 (SD 12.0) mmHg (difference -0.5 mmHg, 95% CI -5.3 to 4.3). No significant between-group differences were observed in secondary outcomes. In post hoc analyses, participants with above-median message reading were more likely to achieve ≥4 of 5 guideline-recommended risk-factor targets at 9 months (69% vs 19.2%; relative risk 3.59, 95% CI 1.57-8.18; P<.001) and logged more diary entries (mean difference 203.4 entries, 95% CI 79.3-327.5; P=.001). BP responders at 9 months read messages on more days than nonresponders (110.3 vs 83.3 d; mean difference 27 d, 95% CI 4.6-49.3; P=.02). Among survey respondents (54/60, 90%), 87% (47/54) found the messages helpful and 81.4% (44/54) wished to continue. Two events occurred in the control group (P=.50). CONCLUSIONS: This trial found no between-group improvement in BP with low-intensity personalized messaging compared to an attention-matched diary app, but exploratory analyses suggest engagement may be a key determinant of potential benefit. Unlike comprehensive app-based cardiac rehabilitation programs, AnSim provides scalable behavioral reinforcement that can be integrated into post-PCI follow-up with minimal burden. These findings support future pragmatic trials optimizing engagement strategies and evaluating longer-term clinical and implementation outcomes.
25 Apr 2026
Read appraisal →Journal of medical Internet research
Perspectives Regarding the Privacy, Security, and Confidentiality of Data Collected via mHealth Apps in Saudi Arabia: Qualitative Analysis
BACKGROUND: As Saudi Arabia aims to enhance the adoption and utilization of mobile health (mHealth) apps in the health care sector, it is vital to identify the potential challenges that may be faced in the process and how to address them. OBJECTIVE: This study aimed to explore patients' and stakeholders' perspectives regarding the privacy, security, and confidentiality of data collected via mHealth apps in Saudi Arabia. METHODS: A qualitative research design was used by conducting an in-depth interview with 25 participants, comprising health care workers (HCWs), patients, and mHealth app developers. The interview questions focused on awareness of mHealth apps and issues relating to data security, privacy and confidentiality, benefits of mHealth apps, challenges faced, and features that may improve the utilization of such digital health technologies. Thematic analysis was performed using NVivo software (version 12; QSR International). RESULTS: Patients were relatively less informed regarding events associated with data privacy and security than HCWs. Specific factors were identified to influence patient awareness with HCWs, suggesting the need for patient education and collaboration with cybersecurity organizations. Participants posited that advanced security features, user-friendly features, online consultation for emergencies, remote monitoring features, and taking patient needs into account are important facilitators of mHealth apps. Shared experiences mainly revolved around the accessibility to information and reliability of mHealth apps, while the challenges were related to poor usability, technical difficulties, data security, and data breaches. Patient autonomy, remote monitoring, self-care management, medical adherence, and time and cost-saving summed up the perceived benefits of the mHealth app. CONCLUSIONS: These findings may assist policymakers in developing strategies to improve Saudi users' and patients' adoption of mHealth apps and address the concerns raised to benefit significantly from these advanced health care modalities.
25 Apr 2026
Read appraisal →Biomedical physics & engineering express
Impact of multimodal information on the estimation of fetal growth indicators using machine learning regression models
Accurate estimation of fetal growth indicators such as birth weight, birth length, and gestational age at birth is essential for monitoring pregnancy outcomes and guiding clinical decisions. Traditional predictive models typically rely on ultrasound-based fetometric data to estimate fetal weight or length. While valuable, these models provide estimates only at the time of measurement, rather than predicting values at birth, and may overlook important clinical and sociodemographic factors that also influence fetal growth. This study aimed to evaluate whether incorporating echographic, clinical, and sociodemographic features could improve the accuracy of predicting fetal growth indicators at birth and to quantify the contribution of each variable. Data from 154 cases were collected and processed for model development (61.5% for training and 38.5% for testing), divided into three feature sets: fetometric, clinical-sociodemographic, and combined clinical, echographic, and sociodemographic data. Six regression models were developed to predict three fetal growth indicators: birth weight, birth length, and gestational age at birth. Model performances were assessed usingR2, mean absolute error (MAE), and mean absolute percentage error (MAPE). The multimodal models significantly outperformed those relying only on fetometric or clinical-sociodemographic data, with the random forest achieving the best performance for birth weightR2: 0.8991; MAE: 255.08 g; MAPE: 8.46%, birth lengthR2: 0.8679; MAE: 7.21 cm; MAPE: 2.73%, and gestational age at birthR2: 0.8886; MAE: 1.34 d; MAPE: 2.76%. Feature relevance analysis revealed that variables such as maternal height, maternal weight, placenta location, and alcohol consumption played substantial roles in prediction accuracy, alongside classic fetometric measurements such as head circumference. These findings highlight the multifactorial nature of fetal growth and demonstrate that integrating clinical and sociodemographic information enhances the performance of fetal growth prediction models, ultimately supporting improved perinatal care.
25 Apr 2026
Read appraisal →JMIR human factors
Personalizing Mobile Apps for Health Behavioral Change According to Personality: Cross-Sectional Validation of a Preference Matrix
BACKGROUND: Mobile health (mHealth) apps are increasingly used to support healthy lifestyle behaviors through features such as health tracking and personalized reminders. Personalized messaging, tailored to users' profiles, has been shown to improve engagement and retention in health-related contexts. Prior research has linked personality traits, based on the Big Five model, to preferences for specific app mechanisms, leading to the development of a preference matrix for personalizing mHealth apps. This matrix comprises 15 mechanisms derived from behavior change techniques and gamification elements, intended to guide developers in optimizing engagement according to user profiles. OBJECTIVE: This study aimed to validate this preference matrix by examining whether the associations between mechanisms and Big Five personality traits reported in the literature align with user preferences observed in an experimental setting. METHODS: A cross-sectional study was conducted using an online survey that collected demographic data, mHealth app usage, and personality traits. Participants were presented with mockups illustrating 15 mechanisms and were asked to select their preferred options. Logistic regression and ordinal logistic regression analyses were performed to examine associations between personality traits, mechanism selection, and motivation scores. All analyses were adjusted using the Bonferroni correction to account for multiple comparisons. RESULTS: A total of 214 participants completed the survey (mean age 29.42, SD 10.41 y; n=118, 55.1% women; n=89, 41.6% men; n=5, 2% identifying as other; and n=2, 1% nonrespondents). Higher conscientiousness significantly increased the likelihood of selecting the collection mechanism (eg, collecting badges or points; odds ratio [OR] 1.87, 95% CI 1.27-2.75). For competition (eg, competing with other users), conscientiousness (OR 3.22, 95% CI 1.73-6.00) and agreeableness (OR 1.93, 95% CI 1.08-3.45) were significant predictors. Preferences for rewards (eg, virtual incentives such as points or virtual currency) were associated with conscientiousness (OR 2.36, 95% CI 1.53-3.63) and neuroticism (OR 1.97, 95% CI 1.36-2.86). Additionally, 4 mechanisms-self-monitoring, progression, challenge, and quest-were selected by more than half of the participants, independent of personality traits. CONCLUSIONS: The findings partially validate the proposed preference matrix. Conscientiousness consistently emerged as a key predictor of preference across multiple mechanisms, highlighting its central role in engagement with gamified mHealth features. While some mechanisms appear to have universal appeal, others show personality-specific preferences, underscoring the value of combining baseline mechanisms with targeted personalization strategies in mHealth app design.
25 Apr 2026
Read appraisal →La Medicina del lavoro
Artificial Intelligence in Occupational Health Surveillance: Evaluating AI-Assisted ILO Classification of Radiographs of Pneumoconioses
BACKGROUND: Pneumoconioses remain an important occupational health issue, particularly in low- and middle-income countries. The International Labour Organization (ILO) Classification standardizes chest radiograph interpretation but requires trained readers and is affected by inter-reader variability. This study evaluated whether generative multimodal artificial intelligence (AI) models can approximate ILO-based diagnostic reasoning. METHODS: Eighty-two chest radiographs from the official NIOSH B Reader syllabus were analysed using four AI systems (GPT-4o, GPT-5, MedGemma-4B, MedGemma-27B). Each image was evaluated with a standardized prompt based on the 2022 revised ILO guidelines using deterministic settings. Model outputs were mapped to ILO codes and compared with the official answer keys of the ILO Standard Radiograph Set used for B Reader training and examination. Performance metrics included balanced accuracy, sensitivity, specificity, precision, and Matthews correlation coefficient (MCC). Bootstrap 95% confidence intervals, McNemar's test, and Cohen's κ assessed performance variability and agreement. RESULTS: All four AI models showed moderate diagnostic performance, with balanced accuracy ranging from 60.8% to 70.3%. Sensitivity remained limited (35.5%-54.9%), while specificity was consistently high (84.6%-86.2%). MedGemma-27B performed best for small opacities, GPT-5 for pleural abnormalities and for technical quality. Large opacities and rare findings were systematically under-detected. Statistical comparisons showed significant differences between models, although agreement patterns were broadly similar. CONCLUSION: All AI models partially followed structured ILO radiographic criteria but did not achieve expert-level performance, confirming that they cannot replace certified B Readers. Larger, real-world datasets are needed to assess their potential clinical utility as supportive tools in occupational health surveillance programs.
25 Apr 2026
Read appraisal →BMJ health & care informatics
Barriers associated with the implementation, adoption, scale-up and sustainability of mHealth in Sub-Saharan Africa: a systematic review guided by the NASSS Framework
OBJECTIVES: The objectives of this study were to highlight and evaluate the factors affecting the non-adoption, abandonment of and challenges to scale-up, spread and sustainability of mHealth in Sub-Saharan Africa (SSA) and to assess the appropriateness of the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) Framework in the SSA context. METHODS: A systematic search of published research was conducted using PubMed and Embase research databases from 2012 to 2025. Peer-reviewed studies from SSA countries, evaluating mHealth interventions, were included in this study. Papers were analysed to identify barriers according to the seven domains of the NASSS Framework, which are (1) condition, (2) technology, (3) value proposition, (4) adopters, (5) organisation(s), (6) wider system, (7) embedding and adaptation over time RESULTS: This study identified 409 barriers across 91 papers. 309 barriers were covered by the seven NASSS Framework domains, while 100 were unaddressed by the framework. The main barriers were associated with domain 2, the technical aspects of the technology (27%). Other prominent barriers related to the wider system (18%), the adopter (11%), the organisation (9%) or condition (8%), with the value proposition (1%) and embedding and adaptation over time (1%), least hindering implementation. Challenges which were unaddressed by the framework (24%) included socioeconomic and infrastructural issues, distinct to lower and middle-income countries (LMIC). DISCUSSION: This paper highlights the importance of evaluating rudimentary aspects of mHealth and preparing infrastructure before addressing more complex issues during mHealth implementation in SSA. CONCLUSION: Although the NASSS Framework is applicable to the SSA region, it would benefit from some further development to improve its applicability in LMICs.
25 Apr 2026
Read appraisal →JMIR human factors
Psychometric Properties of Digital Divide Measurement Instruments in Health Contexts: Systematic Review
BACKGROUND: The digital divide constitutes a growing form of social inequality, influencing access to, use of, and benefit from digital health technologies. Accurate assessment of this phenomenon requires psychometrically sound measurement instruments, especially in health care contexts. OBJECTIVE: This systematic review aimed to identify and evaluate the psychometric properties of instruments developed to measure the digital divide, with a particular focus on their application in health-related settings. METHODS: A systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 and COSMIN (Consensus-Based Standards for the Selection of Health Measurement Instruments) guidelines. Literature searches were performed in PubMed, Scopus, Dialnet, and Web of Science for studies published between 2015 and 2025. Inclusion criteria required studies to report a psychometric evaluation of instruments measuring the digital divide. RESULTS: Four studies met the inclusion criteria (ranging from 875 to 1337 participants). The identified scales primarily measured digital skills and capital. All studies reported adequate internal consistency, with Cronbach α coefficients ranging from 0.70 to 0.94. Structural validity was confirmed through factor analysis in all studies. However, data on temporal stability and responsiveness were absent. CONCLUSIONS: Existing instruments show potential for assessing digital inequality in health, but further psychometric validation and cultural adaptation are required. Nursing professionals are encouraged to lead efforts in developing and validating context-sensitive instruments to promote digital health equity.
25 Apr 2026
Read appraisal →JMIR formative research
Global Mapping of Telemedicine Regulation and Ethical Safeguards: Mixed Methods Exploratory Document Analysis
BACKGROUND: Telemedicine has become central to digital health strategies, yet the regulatory environment that shapes ethical safeguards and equitable access remains uneven and incompletely assessed across countries. Legal and normative instruments matter because they define requirements for privacy, consent, accountability, professional readiness, and barrier reduction. OBJECTIVE: This study aimed to map the current global landscape of normative instruments related to telemedicine and identify which ethical and social safeguards are explicitly addressed, with particular attention to equity. METHODS: We conducted a document analysis guided by the READ (ready the materials, extract data, analyze data, and distill findings) framework. From February 2024 to February 2026, we conducted a structured web-based search across all World Health Organization (WHO) member states with no language restrictions, using official government sources, statutory professional regulators, and institutional publication channels. Retrieval combined internal site searches, direct navigation, external search engine queries, and targeted snowball sampling to identify currently in-force instruments. Two researchers independently extracted and coded data using a predefined codebook. We operationalized 10 binary items covering regulatory presence and scope (questions 1 and 2), safeguards for data protection (question 3), consent and disclosure (questions 4 and 5), prior in-person prerequisites (question 6), monitoring (question 7), training requirements (question 8), and equity (questions 9 and 10). We summarized frequencies overall and stratified by WHO region and World Bank income group and conducted a qualitative thematic analysis of included normative instruments. RESULTS: Of the 194 WHO member states, 81 (41.8%) had at least one current normative instrument related to telemedicine in force. Among these, 72.8% (59/81) defined telemedicine or telehealth. Data protection provisions were most common (73/81, 90.1%), followed by mandatory informed consent (n=71, 87.7%) and monitoring mechanisms (n=65, 80.2%). Fewer countries required disclosure of telemedicine limitations (n=36, 44.4%) or mandated telemedicine-specific training (n=26, 32.1%). Prior in-person consultation requirements were uncommon (n=8, 9.9%). Equity-related safeguards were uneven: 51.9% (n=42) referenced justice, equity, or nondiscrimination, whereas 30.9% (n=25) included concrete barrier reduction provisions (eg, digital inclusion or accommodations for people with disabilities and minors). CONCLUSIONS: Telemedicine regulation is becoming more common, but both coverage and safeguarding content remain uneven. While privacy, consent, and monitoring are frequently addressed where regulation exists, disclosure, physician competency, and operational equity measures are less consistently specified. Strengthening telemedicine governance will require translating ethical commitments into enforceable standards that address digital determinants of access and protect groups at risk of exclusion.
25 Apr 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Computer Vision Models for Detecting Large Cigars on Social Media
INTRODUCTION: Large cigars, which include premium cigars and large manufactured cigars, are widely promoted on social media and digital media, highlighting the critical need for scalable methods to monitor such content. To fill this need, we aimed to train and test an automated computer vision model to identify large cigars. METHODS: In 2022, we obtained 876 large cigar images and 1526 non-cigar images (ie, cigarettes, e-cigarettes, and pens) from Reddit, a global social media platform organized into subcommunities (subreddits) focused on specific topic areas, discussions, and communities. We used the You Only Look Once Version 7 (YOLOv7) computer vision model to train large cigar detection and evaluated its performance using recall, precision, and F1 scores (ie, harmonic mean of recall and precision scores). The data were split into 75% (594 cigar images and 250 non-cigar images) for training and 25% (282 cigar images) for validating and testing. Non-cigar images (n = 1276) were used to evaluate for false positives. RESULTS: Our model achieved a recall of 0.98, a precision of 0.99, and an F1 score of 0.98, demonstrating high accuracy in correctly identifying large cigars while minimizing false positives. It successfully distinguished large cigars from similarly shaped objects with an accuracy of 97%. CONCLUSIONS: Our computer vision model accurately distinguished large cigars from non-cigar images, demonstrating its potential as an automated, scalable tool for monitoring this understudied tobacco product on social media and other digital media. IMPLICATIONS: This computer vision model offers a novel and scalable approach to tobacco monitoring by automatically detecting large cigars in social media content. Its application may enhance the efficiency of product identification and facilitate research on use patterns, user perceptions, and emerging marketing strategies, thereby generating evidence to inform regulatory decision-making and policies aimed at preventing initiation.
24 Apr 2026
Read appraisal →PloS one
Forecasting under-five stunting in Ethiopia using classical and machine learning time series models
BACKGROUND: The prevalence of under-five stunting in Ethiopia remains above 30%, which, according to World Health Organization (WHO), constitutes a major public health concern. Stunting has long-term consequences for child growth, development, and overall health. Accurate forecasting of its prevalence is therefore essential to guide policymakers and inform targeted interventions. This study aimed to forecast the prevalence of under-five stunting in Ethiopia for the period 2025-2030 using historical data and time series modeling. METHODS: Annual under-five stunting prevalence data for Ethiopia from 2000 to 2024 were retrieved from the WHO Global Health Observatory. Time series forecasting models, including Autoregressive Integrated Moving Average (ARIMA), Exponential Smoothing (ETS), Multilayer Perceptron (MLP), and Long Short-Term Memory (LSTM), were developed and evaluated. Model performance was assessed using time series cross-validation with mean absolute error (MAE), mean absolute percentage error (MAPE), and R² as evaluation metrics. The best-performing model was applied to forecast stunting prevalence for 2025-2030. RESULTS: The ETS model demonstrated the best predictive performance (MAE = 1.09, MAPE = 2.71%, R² = 0.903) and was selected for forecasting. Forecasting indicated a gradual decline in under-five stunting prevalence in Ethiopia from 33.95% in 2025 to 31.95% in 2030. The projected prevalence for 2029 is 32.35% (95% CI: 26.90-37.79%), above the national target of 19%, and the 2030 forecast remains well above the SDG target of ending all forms of malnutrition. CONCLUSION AND RECOMMENDATION: Under-five stunting in Ethiopia is projected to remain above national and SDG targets by 2030, indicating current nutrition efforts are insufficient; national program evaluation and evidence-based policy adjustments are recommended.
24 Apr 2026
Read appraisal →PloS one
Hepatitis C distribution across diverse population groups in the Eastern Mediterranean Region: An umbrella review
BACKGROUND: Hepatitis C virus (HCV) remains a major public health challenge in the Eastern Mediterranean Region (EMR), with prevalence varying across population groups. This umbrella review summarizes the distribution of HCV infection across diverse populations in the region. METHODS: We conducted an umbrella review of systematic reviews with meta-analyses reporting HCV prevalence in the EMR. PubMed, Web of Science, Scopus, Iranian databases, including Magiran and the Scientific Information Database (SID), were searched. Google Scholar was additionally screened to ensure comprehensive coverage. Pooled estimates were extracted across four population groups: apparently healthy individuals; those with clinical or healthcare-associated exposure risk; patients co-infected with hepatitis viruses or other liver-related diseases; and key populations at increased risk (groups disproportionately affected due to their behaviors and higher vulnerability). For time-period analyses, meta-analyses were grouped into two intervals (before 2015 vs. 2015 and after) based on the median year of data collection of primary studies. Pooled prevalence was calculated using a random-effects model in STATA version 17. RESULTS: A total of 55 meta-analyses were included. The pooled HCV prevalence was 31.0% (95% CI: 27.0-38.0) among key populations, and also 31.0% (95% CI: 12.0-49.0) among patients co-infected with other hepatitis viruses or liver-related diseases. Those with clinical or healthcare-associated exposure risk showed a prevalence of 28.0% (95% CI: 23.0-32.0), whereas the apparently healthy population had the lowest prevalence at 2.0% (95% CI: 1.0-2.0). Subgroup analysis indicated a decline in prevalence among clinically exposed populations after 2015, from 29% to 10%, coinciding with the direct-acting antivirals (DAAs) and strengthened infection-control practices. The highest prevalence was observed among key populations in Libya, healthcare-exposed populations in Morocco, and apparently healthy individuals in Egypt. CONCLUSION: Variation in HCV prevalence across populations in the EMR highlights the need for population-specific strategies to support progress toward World Health Organization elimination targets.
24 Apr 2026
Read appraisal →JMIR formative research
Access to Technology-Mediated Community Mental Health Care Among Low-Socioeconomic Status Consumers With Serious Mental Illness: Qualitative Study
BACKGROUND: Access to mental health care is critical for the effective management of serious mental illness (SMI), but consumers with low socioeconomic status (SES) have lower rates of service usage and worse retention in care. Digital technologies are often lauded as a way to bridge access gaps; however, little is known about how technology-mediated care may influence care access among low-SES consumers and how consumers use technology in care access. OBJECTIVE: This study aimed to examine the applicability of Levesque et al's access framework to technology-mediated care for SMI and analyze how low-SES consumers use technology to facilitate care access. Furthermore, the study assesses whether and how technologies are involved in care access at multiple points within the process of accessing care. METHODS: This study used 2 qualitative methods: ethnographic observations at a mental health treatment court and interviews with low-SES consumers with SMI using community mental health care (n=14) and key informant interviews with health and service providers working with this population (n=14). Observations occurred from July 2022 through September 2023, and interviews occurred between January 2022 and May 2024. Data analysis involved both inductive and deductive coding approaches. Data from both the interviews and observations were analyzed in NVivo and further triangulated through analytic memos. RESULTS: Levesque et al's framework required several extensions to accommodate technology-mediated care related to SMI for low-SES consumers: (1) a cyclical rather than linear trajectory; (2) simultaneous care acquisition from multiple health and service providers; (3) staying in care long-term; (4) identification of both one-time and ongoing health needs; and (5) an emergency pathway for entering care. Consumers often faced challenges related to the varied digital requirements of each provider and a dearth of integrative, patient-facing tools like portals. Within this context, some consumers use mobile apps, communication, and telehealth technologies across various care access stages. Consumers used technology by figuring out how to navigate technology-mediated care, especially by leaning on others, such as case managers, for support. These others provided consumers with temporary technologies, showed them how to use technologies, and accompanied them through the process of using technology for accessing care. CONCLUSIONS: This study highlights that accessing care is iterative and ongoing, involving multiple forms of co-occurring service provision. A theoretical contribution of this work is its extension of Levesque et al's care access framework to better reflect technology-mediated care for SMI among low-SES consumers. This work also underscores ongoing challenges for accessing technology-mediated care and the importance of human support in addressing access difficulties. Clinical implications include incorporating digital readiness assessments and providing comprehensive guidance on how consumers can effectively use technologies for care. Future work should investigate how technology-mediated care can make care access easier rather than harder.
24 Apr 2026
Read appraisal →Annals of medicine
The effect of nutrition education interventions on dialysis patients' outcomes: a systematic review and meta-analysis
BACKGROUND: Non-adherence to dietary and fluid restrictions among dialysis patients is associated with adverse clinical outcomes. Quantifying the effectiveness of nutrition education interventions can inform practice and policy. METHODS: We searched MEDLINE, EMBASE, CINAHL, CENTRAL, PsycINFO, Web of Science, and Scopus up to 15 July 2025, supplemented by trial registries and Google Scholar, with an updated search through 8 April 2026. Eligible studies included randomized and non-randomized trials evaluating nutritional education interventions in adult dialysis populations. Risk of bias was assessed using RoB-2 and ROBINS-I, certainty graded using GRADE, and random-effects meta-analyses conducted alongside subgroup, sensitivity, and meta-regression analyses. Publication bias was assessed with Egger and Begg tests and trim-and-fill where applicable. RESULTS: Forty-four studies comprising 4,106 participants were included. Nutrition education significantly improved knowledge (SMD = 1.09; 95% CI: 0.67-1.51) and health-related quality of life (SMD = 1.43; 95% CI: 0.86-2.00; I² = 0%), and reduced serum potassium (SMD = -0.52; 95% CI: -0.91 to -0.14; I² = 92%) and serum phosphate (SMD = -0.35; 95% CI: -0.56 to -0.15; I² = 81%). Results for albumin, creatinine, sodium, calcium, and BUN were inconsistent and non-significant. Most outcomes were rated low or very low certainty by GRADE, reflecting inconsistency, indirectness, and imprecision. Potential publication bias was identified for certain outcomes. CONCLUSIONS: Nutrition education consistently improves knowledge and quality of life and may modestly reduce serum phosphate and potassium in dialysis patients. High-quality registered trials with standardized outcomes and longer follow-up are needed to establish effectiveness and sustainability. PROSPERO REGISTRATION: CRD420251119567.
24 Apr 2026
Read appraisal →ACS applied materials & interfaces
Flexible, Scalable SERS Substrate with High Sensitivity and Stability for On-Site Detection and Wearable Applications
A key challenge in the commercialization of surface-enhanced Raman scattering (SERS) technology is the scalable and controllable preparation of substrates that simultaneously achieve high sensitivity, uniform signal distribution, excellent reproducibility, and long-term stability. In this study, we report a flexible SERS substrate based on a porous, high-surface-energy nanofilm, designed to serve as a spatially confined template for the uniform growth of silver nanoparticles (AgNPs). This substrate exhibits outstanding SERS performance with an enhancement factor (EF) of 2.05 × 1010 and a detection limit (DL) as low as 1.74 × 10-15 M for rhodamine 6G (R6G). The preparation process is mild, highly reproducible (RSD = 8.53% over 60 consecutive batches), and scalable to 25 cm2 areas. Moreover, the substrate maintains its SERS activity for over three months within a vacuum bag at room temperature. Owing to its excellent adhesion and good flexibility, the substrate can adhere effectively to complex surfaces. The substrate was successfully applied to sensitive in situ detection of trace thiram residues on grape surfaces, achieving a detection limit (DL) of 8.51 × 10-10 g cm-2. Additionally, a wearable sensor was developed based on the substrate and used for the noninvasive monitoring of uric acid levels in human sweat, with a DL of 2.95 × 10-7 M. This work provides a practical strategy for constructing high-performance, scalable, and flexible SERS substrates, advancing their potential for real-time, on-site analysis.
23 Apr 2026
Read appraisal →Journal of Korean medical science
Association Between Changes in Socioeconomic Status Before and After Human Immunodeficiency Virus Infection Diagnosis and Mortality Rates in Korea
BACKGROUND: This study investigated changes in medical insurance status as a surrogate marker of socioeconomic status after human immunodeficiency virus (HIV) infection, and their association with mortality among people living with HIV in Korea. METHODS: This study included 13,112 individuals newly diagnosed with HIV between 2004 and 2018, identified from the claims data of the National Health Insurance System-National Health Information Database. Participants' medical insurance status was categorized into National Health Insurance (NHI) and medical aid (MA). Using the Cox proportional hazards model, the association between mortality and changes in medical insurance status before and after HIV infection diagnosis was assessed using hazard ratios (HRs) and confidence intervals (CIs). RESULTS: The insurance coverage rates before HIV diagnosis were 95.1% and 4.9% for NHI and MA recipients, respectively. After diagnosis, the insurance coverage rates were 13.4% and 86.6% for MA and NHI recipients, respectively, demonstrating a threefold increase in the proportion of MA recipients. The conversion rate from NHI to MA was highest in the 35-44 and 45-54-year age groups at HIV infection diagnosis (32.9% and 29.4%, respectively). Compared with NHI recipients, the HR was significantly higher among individuals that transitioned from NHI to MA (HR, 1.66; 95% CI, 1.39-1.97) and individuals that remained on MA (HR, 1.74; 95% CI, 1.40-2.18), suggesting a higher mortality rate in these groups. CONCLUSION: In Korea, where highly active antiretroviral therapy is essentially free of charge, a significant association was observed between a decline in medical insurance status following HIV diagnosis and increased mortality.
23 Apr 2026
Read appraisal →PloS one
Understanding older adults' perception, acceptance, and adoption of smart home technologies
Smart home technologies have increased in popularity and affordability in recent years, however, there is limited research on their adoption specifically among older adults. This study aims to uncover incentives and barriers to the adoption of smart home components, given the impact of COVID-19 on older adults' quality of life (QoL). For this purpose, online audio-recorded interviews were conducted with 21 participants aged between 65 and 90 years from the UK, Malta, and Pakistan. Participants were shown various smart home technology images and videos and asked for their perception, existing knowledge, and current use. The corresponding audio recordings were transcribed and thematically analysed. Findings revealed that older adults experienced a decline in QoL during COVID-19, accompanied by an increased reliance on digital technologies. While participants recognised the potential of smart home devices to enhance independence and well-being, their knowledge of available options was limited. Key barriers included affordability, privacy and trust concerns, compatibility and integration issues, and environmental and social considerations. Cross-cultural differences emerged, with European participants reporting higher familiarity than those in Pakistan, particularly rural areas where availability was limited. These results highlight the need for designers and policymakers to improve affordability, usability, and cultural adaptability in order to support older adults' acceptance and meaningful adoption of smart home technologies.
23 Apr 2026
Read appraisal →PloS one
Prevalence of antimicrobial resistance in Tanzania: A systematic review and meta-analysis
Antimicrobial resistance (AMR) threatens global health, and understanding resistance patterns aids in effective treatment and promotes responsible antimicrobial use. Despite the urgency of resistant pathogens, systematic reviews focusing specifically on Tanzania are limited, and while several studies report resistance patterns for individual pathogens, a consolidated analysis of overall prevalence is needed to inform policymaking and public health interventions. Therefore, this review and meta-analysis assessed the prevalence of antimicrobial resistance among clinically relevant pathogens in Tanzania, providing a comprehensive overview to support surveillance, infection control, and stewardship efforts. A total of 1865 studies identified from Google Scholar (1600), PubMed (13), and Science Direct (252) underwent screening and full article review. Finally, 28 studies were included. A subgroup analysis was performed to evaluate the resistance patterns within antibiotic classes for specific pathogens. Descriptive statistics were used to describe the characteristics of the studies, while the prevalence of antimicrobial resistance was estimated through Meta-analysis. Inconsistency and heterogeneity between studies were quantified by the I2 index. Among the included studies, most isolates (25.0%) were obtained from urine samples. Of these studies, 75% were cross-sectional studies and 92.9% were conducted in hospital settings. The analysis revealed high resistance to penicillin, particularly amoxicillin-clavulanic and ampicillin, with Klebsiella pneumoniae (0.96 [0.83-0.99]), Acinetobacter baumannii (0.94 [0.67-0.99]) and Escherichia coli (0.90 [0.81-0.95]). Similarly, erythromycin resistance was most prevalent in Campylobacter spp. (0.85 [0.80-0.89]). Ciprofloxacin resistance was highest in Acinetobacter baumannii (0.54 [0.33-0.73]), whereas amikacin resistance was highest in Proteus spp. (0.86 [0.35-0.99]). Ceftriaxone resistance was particularly high in Acinetobacter baumannii (0.91 [0.70-0.98]) and Pseudomonas aeruginosa (0.85 [0.74-0.92]). Meropenem resistance was lowest among Escherichia coli (0.04 [0.01-0.10]) and Klebsiella spp. (0.07 [0.03-0.15]), while the pooled resistance across ESKAPE-E pathogens was (0.11[0.06-0.19]). Imipenem and clindamycin each had an overall pooled resistance of (0.06[0.02-0.14]) against both Escherichia coli and Klebsiella pneumoniae. The findings highlight widespread resistance among bacterial pathogens, ESKAPE-E, particularly in the Access and Watch groups of antibiotics. The variability in resistance patterns underscores the need for the Ministry of Health to re-evaluate empirical treatment protocols (STG/NEMLIT) to ensure effective treatment regimens, strengthen antimicrobial stewardship, enhance surveillance systems, and promote rational antibiotic use.
23 Apr 2026
Read appraisal →Medical education online
Medical students' attitudes towards older persons - a systematic review and meta-analysis
OBJECTIVE: Ageism negatively affects older people's health, well-being, and quality of care. Identifying ageism and attitudes toward older adults may help identify medical students motivated to work with a growing older population. We conducted a systematic review of interventions to reduce ageism among medical students. METHODS: We conducted a systematic literature retrieval in Medline, the Cochrane Library, Epistemonikos and PubMed via Ovid, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, from database inception to August 23rd, 2024. We searched for studies examining medical students' attitudes towards older persons, including interventions to influence these attitudes. RESULTS: The systematic review included 21 studies. Study samples ranged between 29 and 415, with a pooled total of 3940 medical students, the majority conducted in the USA. The meta-analysis of students' attitudes before and after all interventions included a total of 2004 students, yielding a non-significant standardized mean difference (SMD) of 0, 12 (95% CI -0, 01 to 0, 26). The meta-analysis of students' attitudes before and after all interventions (35-37, 39, 41, 45, 48, 50), after removing UCLA-GAS and R-GAS, included a total of 1344 students with a standardized mean difference of 0, 23 (95% CI 0, 06 to 0, 40). Analysis of empathy-based teaching interventions included 1652 students, and showed a statistically significant effect, SMD 0, 18 (95% CI 0, 01 to 0, 34). Analysis of 352 students receiving traditional teaching methods yielded no effect on ageism, with an SMD -0, 13 (95% CI -0, 81 to 0, 54). High heterogeneity (I2 75-85%) affects our confidence in the effect estimates. CONCLUSION: Empathy-based interventions seem to improve medical students' attitudes towards older persons. Traditional teaching methods may increase negative attitudes. Considering the high heterogeneity, the results should be interpreted cautiously. Adding empathy-based components to medical curricula could combat ageism. More studies are needed to examine whether the results of studies from North America are valid globally.
23 Apr 2026
Read appraisal →Journal of Korean medical science
Comparison of the Hearing Benefits and User Satisfaction With Hearing Aids and Personal Sound Amplification Products: A Multicenter Prospective Randomized Crossover Trial
BACKGROUND: While hearing aids (HAs) remain the primary intervention for hearing loss, their high cost creates barriers to access. Personal sound amplification products (PSAPs) are a more affordable alternative, but few studies have compared their efficacy to those of HAs. This multicenter, prospective, randomized, crossover trial was conducted to compare audiologic performance and user satisfaction between HAs and PSAPs to evaluate PSAP potential as alternatives for hearing rehabilitation. METHODS: A total of 73 participants with sensorineural hearing loss was enrolled. Participants used one hearing device (HA or PSAP) for 3 months before changing to the other for 3 months. Outcome measures were pure-tone audiometry, word recognition score, and Hearing in Noise Test score. Subjective satisfaction was measured using standardized questionnaires-the Abbreviated Profile of Hearing Aid Benefit and the International Outcome Inventory for Hearing Aids-and two custom surveys. RESULTS: HAs showed superior performance in high-frequency functional gain, speech perception in noise, and user satisfaction compared to PSAPs. Premium HAs demonstrated better performance than basic HAs, while basic HAs significantly outperformed both high-end and basic PSAPs. No significant differences were found between high-end and basic PSAPs. CONCLUSION: The superior audiologic performance of and user satisfaction with HAs compared to PSAPs support their continued preference for hearing rehabilitation. Although PSAPs offer a more affordable option, they may not meet the needs of individuals with hearing loss, particularly in terms of high-frequency gain and speech perception. TRIAL REGISTRATION: iCreaT Identifier: C220078.
23 Apr 2026
Read appraisal →PloS one
An AI-based chatbot to support health-related social needs among pediatric primary care population: Protocol for a pilot randomized controlled trial
Unmet health-related social needs (HRSNs) are major drivers of poor health outcomes in early childhood. Children with unmet HRSNs are at greater risk for developmental delays, caregiver stress, and increased healthcare utilization, yet current screening approaches in pediatric primary care are resource-intensive and inconsistently implemented. AI-powered chatbots (conversational agents or virtual assistants) may offer a private, secure, scalable, and cost-effective alternative for identifying unmet needs and connecting families to services. This protocol describes a pilot randomized controlled trial designed to evaluate the feasibility, acceptability, and usability of DAPHNE, an AI-driven chatbot developed to facilitate the identification of unmet HRSNs and provide personalized community resource referrals. One hundred caregivers of children under two years of age will be recruited from Nationwide Children's Hospital pediatric primary care clinics and randomized to either the standard care (control) group or DAPHNE+ Standard care (intervention) group (n = 50 each arm). Caregivers will complete surveys at baseline, 1 month, 3 months, and 6 months post-intervention (depending on the measure). For the intervention group, participants will receive weekly chatbot prompts and on-demand access throughout the 6-month study period. Primary outcomes include study feasibility (recruitment, retention, and survey completion across both arms), acceptability (caregiver-reported ratings in both arms and intervention-specific ratings), and usability of the DAPHNE chatbot (System Usability Scale among intervention participants). Secondary outcomes includes caregiver-reported outcome measures (caregiver stress, self-efficacy, satisfaction with resource access, quality of life), and electronic health record-derived measures (including documentation of HRSN screening and referrals, adherence to well-child visits, missed appointments, emergency department utilization, and estimated healthcare costs). In addition, ten primary care providers will also participate to assess workflow integration and report on current HRSN practices. Mixed-methods analyses will integrate survey data, chatbot engagement metrics, and qualitative interviews to refine both the intervention and the study protocol. The results of this study will inform the design of a future multi-site trial to evaluate the efficacy and implementation of DAPHNE for addressing HRSNs in pediatric primary care. Trial registration: NCT07168382.
23 Apr 2026
Read appraisal →Veterinaria italiana
A One Health systematic review and meta-analysis of Coxiella burnetii prevalence in humans, animals, and vectors in Algeria
Coxiella burnetii, the causative agent of Q fever, is a globally distributed zoonotic pathogen affecting humans, domestic animals, and arthropod vectors. In Algeria, fragmented data suggest widespread circulation, yet no comprehensive quantitative assessment exists. This study aimed to systematically review and meta-analyse the prevalence of C. burnetii in humans, animals, and vectors in Algeria, using a One Health perspective. A systematic search of PubMed, Scopus, Web of Science, and Google Scholar was conducted up to January 2026. Studies reporting serological or molecular detection of C. burnetii in Algeria were included. Random-effects meta-analysis was performed to estimate pooled prevalence, with subgroup analyses by host species, region, and diagnostic method. A total of 35 studies were included, encompassing 8,372 samples and 80 prevalence observations. Pooled prevalence was highest in camels (73.7%; 95% CI: 66.5-79.8%), followed by small ruminants (15.8%; 95% CI: 10.6-22.9%) and cattle (11.8%; 95% CI: 7.2-18.8%). Ticks showed a pooled prevalence of 10.0% (95% CI: 3.2-27.1%), while human infection had a pooled prevalence of 3.7% (95% CI: 0.9-13.9%). The south-eastern region exhibited the highest prevalence, and serological methods generally reported higher rates than molecular methods. High heterogeneity (I² > 75%) was observed across studies. Coxiella burnetii is widely circulating among humans, domestic animals, camels, and ticks in Algeria, with notable variation between hosts and regions. Camels and small ruminants act as major reservoirs, while humans remain at risk, particularly those in close contact with livestock. Integrated One Health surveillance and targeted control strategies are urgently needed to reduce the burden of Q fever.
22 Apr 2026
Read appraisal →JMIR research protocols
WhatsApp-Led mHealth Intervention for Hypertension Management Among Adults Aged 40 to 59 Years in Kerala, India: Protocol for a Mixed Methods Study
BACKGROUND: Medication adherence and lifestyle modification remain key in the management of hypertension. Leveraging mobile technologies to improve patient adherence has been found to be effective in chronic disease management. Given the high mobile penetration and the opportunities it provides for encouraging lifestyle modification, an app such as WhatsApp, which is a free-to-use and real-time messaging platform, could facilitate patient-clinician interactions. We present a protocol for a WhatsApp-led mobile health (mHealth) intervention to improve adherence to medication and healthy lifestyles among adults aged 40 to 59 years in Kerala, India. OBJECTIVE: The study aims to assess the impact of the WhatsApp-led mHealth strategy on blood pressure measures and adherence to medication and lifestyle modification. The study also focuses on exploring participants' views on feasibility, facilitators, and challenges, as well as their intention to use this WhatsApp-led mHealth strategy. METHODS: The study will follow a multiphase mixed methods (sequential explanatory) design with an initial quantitative phase (quasi-experimental study design) followed by a qualitative phase (phenomenological approach). Multistage cluster sampling will be adopted. Using a survey checklist and blood pressure measurements, community-dwelling adults aged 40 to 59 years will be screened for hypertension. Approximately 120 participants with hypertension will be assigned each to the intervention and control arms. All the participants will be advised to follow routine hypertension care from health care providers. Additionally, participants in the intervention arm will receive regular health messages and reminders over WhatsApp. A baseline survey will be conducted at enrollment, and a follow-up survey will be conducted after 3 months at the end of the intervention. The qualitative phase will involve follow-up interviews. Participants will be selected through quota sampling from those with the lowest and highest adherence to medication and lifestyle modification after receiving the intervention. Statistical analysis for survey data and thematic analysis for qualitative data will be conducted. RESULTS: The study received ethics approval (IHEC/CUK/2024/04) from the Institutional Human Ethics Committee of the Central University of Kerala. All 240 participants were recruited by July 2025. The study completed data collection in August 2025 and is expected to finish data analysis by April 2026. The study results are expected to be submitted for publication in July 2026. CONCLUSIONS: The study will be a potential strategy to address nonadherence to treatment and lifestyle regimens, which is a critical bottleneck to controlling hypertension and preventing complications. The study could be proof for a WhatsApp-led mHealth strategy that can be integrated into hypertension management at the community level, especially for improving hypertension awareness and reminders for behavior change.
22 Apr 2026
Read appraisal →JMIR infodemiology
Cross-Sectional Evaluation of Medical Disinformation Safeguards in Consumer-Facing Large Language Model Platforms
This cross-sectional evaluation of six consumer-facing large language model platforms found significant heterogeneity in safeguard performance against the generation of health disinformation, with Claude and ChatGPT demonstrating complete resistance across all prompt types, while Copilot, Meta AI, Grok, and Gemini exhibited substantial vulnerabilities.
22 Apr 2026
Read appraisal →PloS one
Global folate deficiency among adolescent girls: A systematic review and meta-analysis
INTRODUCTION: Adolescents have higher nutrient requirements than adults, as this stage accounts for approximately 40% of total adult weight gain, 45% of skeletal mass and about 15% of adult height. Adequate micronutrient intake is particularly essential for adolescent girls to support growth, reproductive health, and cognitive development. Adolescent folate deficiency disrupts hematopoiesis, causing megaloblastic anemia, and hinders growth, cognition, and immune function and becoming a major public health concern. OBJECTIVE: This global systematic review and meta-analysis aims to address the gap in comprehensive evidence on the prevalence of adolescent folate deficiency. METHODS: This systematic review was conducted and reported according to PRISMA guidelines. We conducted a systematic literature search in PubMed, HINARI, Science Direct, DOAJ, Google, and Google Scholar for studies reporting the prevalence of folate deficiency among adolescent girls up to August 2025. Study quality was assessed using the Newcastle-Ottawa Scale, and evidence certainty was evaluated using GRADE. Pooled prevalence estimates with 95% confidence intervals were calculated using a random-effects model (DerSimonian-Laird method). Heterogeneity was assessed with Cochrane Q and I² statistics. Publication bias was evaluated through visual inspection of funnel plots and Egger's regression test, and adjusted estimates were calculated using the trim-and-fill method. Meta-regression analyses were conducted to explore potential sources of heterogeneity. Sensitivity analyses were performed to assess the robustness of pooled estimates. RESULTS: The search strategy identified 1,498 records, of which 26 studies met the eligibility criteria and were included in this systematic review and meta-analysis. The pooled global prevalence of folate deficiency among adolescent girls was 26.9%(95% CI: 20.5-33.2), with substantial heterogeneity observed between studies (I² = 99.99%, p < 0.001). On average across included studies, approximately one-quarter of adolescent girls were classified as folate deficient, though the true prevalence varied markedly between settings.. The pooled prevalence of folate deficiency among adolescent girls varied across regions, with the highest rate observed in Africa at 35.5%. CONCLUSION: These findings revealed folate deficiency as a substantial global public health concern among adolescent girls with a disproportionately high burden in low-resource settings. Region-specific strategies are urgently needed to prevent folate deficiency among adolescent girls, particularly in low-resource settings. Implementing targeted nutritional interventions and public health policies is essential to reduce its associated health consequences in this vulnerable population.
22 Apr 2026
Read appraisal →Journal of neurology
The association of night shift work with the risk of acute ischemic cerebrovascular syndrome: a longitudinal study of 204,261 UK Biobank participants
BACKGROUND: Shift work is highly prevalent globally, yet evidence linking it to ischemic cerebrovascular disease remains inconsistent. Existing studies are limited by unsystematic quantification of night shift exposure and outcome definitions failing to capture the clinical continuum of ischemic events. We performed a large prospective cohort study using refined shift pattern classification and acute ischemic cerebrovascular syndrome (AICS) as the primary end point to enable a robust evaluation of the association between shift patterns and ischemic cerebrovascular disease. METHODS: 204,261 participants with employment information from the UK Biobank were included. Cox proportional hazards regression was used to assess associations between current shift work and AICS risk, with cross-classification by shift status and job duration. We further quantified average lifetime night shift frequency and cumulative duration among participants with complete occupational histories. Transient ischemic attack (TIA) and ischemic stroke (IS) were analyzed separately to identify the main driver of AICS and potential heterogeneity. RESULTS: During a median follow-up exceeding 14 years, irregular shift work was significantly associated with elevated AICS risk (HR 1.118, 95% CI 1.019-1.227, P = 0.019), while always night shift work was not (HR 0.904, 95% CI 0.707-1.157, P = 0.423). AICS risk was driven by irregular shift patterns rather than duration. Lifetime night shift frequency and duration showed significant dose-response relationships with AICS. CONCLUSIONS: Irregular shift work increases AICS risk relative to non-shift work, and lifetime night shift exposure exhibits a clear dose-response effect. IS constitutes the primary driver of the composite AICS end point.
20 Apr 2026
Read appraisal →International journal of biometeorology
Random forest-based medical geography: geographical distribution of reference values for LP-PLA2 in healthy adults in China
Lipoprotein-associated phospholipase A2 (LP-PLA2), a vascular-specific inflammatory marker, is associated with coronary heart disease (CHD), a highly prevalent condition among middle-aged and older adults. It explores the relationship between environmental factors in environmentscience, geography, statistics and medicine and the reference value of LP-PLA2 in China. A geographic distribution prediction model for Lp-PLA2 medical reference values was developed using optimized machine learning approaches. The support vector machine (SVM) model employed a polynomial kernel function, with hyperparameters tuned via grid search and cross-validation to determine the optimal classifier configuration. Concurrently, the random forest algorithm was applied to mitigate overfitting and perform regression analysis on the dataset. Further considering the influence of geographical factors on the 100 LP-PLA2 medical reference values in city and county units from 2000 to 2024, using 24 geographical factors as independent variables, to fit 2317 LP-PLA2 medical reference values, and then explore the spatial variation characteristics of LP-PLA2 medical reference values. Further spatial interpolation was visualized on the national map. The medical reference value of LP-PLA2 was significantly correlated with longitude, altitude, annual average wind speed, topsoil clay percentage, topsoil reference capacity, topsoil organic matter content, and total convertible amount of topsoil, respectively. The geospatial distribution map shows that the whole value was high in the east and low in the west, with significant differences in longitude. The geographical characteristics of any given region, when analyzed through either the SVM prediction model or the derived geographical distribution map, enable precise determination of region-specific Lp-PLA2 reference values. This establishes an evidence-based foundation for clinical decision-making and research design in healthcare institutions and medical research organizations.
20 Apr 2026
Read appraisal →International journal of epidemiology
Structured tools for assessing quality and risk of bias in Mendelian randomization studies: an updated systematic review
BACKGROUND: The growing use of Mendelian randomization (MR) has heightened the need for rigorous quality and bias assessment tools. A previous systematic review included studies published up to July 2021 identified 14 structured instruments for conducting, evaluating, and reporting MR studies. However, methodological developments have accelerated in the years since. METHODS: We updated the previous systematic review to include tools published between July 2021 and January 2025, applying the same search strategy and eligibility criteria. Two reviewers independently screened articles, extracted data, and mapped tool content to bias domains. RESULTS: We identified 15 additional articles, bringing the total to 29 tools. Of these 29, 19 provided structured evaluation tools. Twelve of the 19 evaluation tools were newly added in the present review, which addressed broader methodological domains beyond core instrumental variable assumptions, including genetic instrument selection, population stratification, sensitivity analyses, and dataset considerations. However, substantial variation in bias domains, structure, and scoring methods across tools persists. Key gaps remain in the assessment of linkage disequilibrium, missing data, and dynastic effects. CONCLUSIONS: While the number of structured tools has increased in recent years, the lack of standardization across tools makes it difficult to compare across systematic reviews of MR studies. Developing more complete and standardized evaluation frameworks and properly testing these tools in practice are important next steps to improve the overall quality of MR research.
20 Apr 2026
Read appraisal →Journal of medical Internet research
Facility-Level Associations Between Use of a Digital Health Platform for Voluntary Counseling and Testing and HIV Testing Outcomes in the Urban Primary Health Care Centers of Guangzhou, China: Cross-Sectional Study
BACKGROUND: WellTest, a digital health platform designed to facilitate HIV voluntary counseling and testing (VCT) services, has been widely implemented in Guangzhou, China. However, the extent of its use by primary health care centers (PHCs) and the facility-level associations between WellTest use and HIV testing outcomes remain unclear. OBJECTIVE: This study aimed to assess the use of WellTest at the facility level across PHCs in urban Guangzhou, China, and to explore the associations between WellTest use and HIV testing outcomes. METHODS: We obtained data on VCT services visits from the National HIV/AIDS Prevention and Control Information System and the WellTest platform between January 1 and December 31, 2022. Two facility-level HIV testing outcomes, the HIV testing volume and HIV positivity rate, were calculated for each PHC. A structured questionnaire collected data on the PHCs' characteristics. Multilevel negative binomial regression and zero-inflated gamma models were used to examine associations between WellTest use and 2 HIV testing outcomes at the facility level. RESULTS: A total of 81 PHCs across 5 urban districts in Guangzhou were included. WellTest was used for 7997 active consultations and 7969 HIV tests that resulted in 157 newly diagnosed HIV cases, for an overall positivity rate of 2.0%, during 2022. The median share of clients booking via WellTest was 71% (IQR 34%-98%), and 81% (66/81) of PHCs offered online slots on all service days without mandates. PHCs that actively confirmed appointments had significantly lower HIV testing volumes compared with those that took no actions after clients scheduled appointments (incidence rate ratio 0.75, 95% CI 0.58-0.97; P=.03) but exhibited higher HIV positivity rates (β=.39, 95% CI 0.02-0.76; P=.04). Additionally, PHCs where ≥50% of clients used WellTest to schedule appointments showed higher HIV positivity rates than those with lower uptake (β=1.11; 95% CI 0.82-1.40; P<.001). CONCLUSIONS: WellTest showed substantial use among VCT clients and providers in urban Guangzhou PHCs, with greater use of digital appointments and counselor follow-up linked to increased HIV positivity rates. Strategies to optimize institutional adoption may help address stigma-related barriers, strengthen engagement in HIV testing, and support HIV case finding in primary health care settings.
20 Apr 2026
Read appraisal →BMJ open respiratory research
Comparing paper Letters in addition to Emailed Audit and feedback in Refining Asthma treatment to Improve clinical and environmental Results in primary care through a cluster randomised controlled trial: the CLEAR AIR study
BACKGROUND: Suboptimal use of preventer inhalers and salbutamol reliever overprescribing are associated with preventable asthma deaths and are a major source of primary care carbon emissions. Audit and feedback produces modest behaviour change by assessing clinical performance and delivering feedback to encourage improvement. Although feedback is increasingly delivered digitally, clinicians may respond more to additional printed feedback reports. We evaluated whether combined digital and paper feedback was more effective than digital-only feedback in promoting safer and greener asthma prescribing at the practice level. METHODS: In this parallel, cluster randomised controlled trial, all 273 primary care practices in West Yorkshire were assigned within their primary care network clusters by stratified, permuted block randomisation to receive seven bimonthly reports on asthma prescribing either in 'digital and paper' (intervention) or 'digital-only' (control) formats. The primary outcome was the proportion of preventer inhalers prescribed in pressurised metred-dose devices due to their high carbon footprint. Intervention group allocation was concealed. The intention-to-treat population was analysed and adjusted for both potential confounders and preintervention achievement. RESULTS: Final analysis assessed 270 practices in 26 clusters per arm due to practice mergers within the control group. There was no significant difference between the intervention groups based on change in the primary outcome (intervention-0.15%; control-0.19%; risk ratio-1.00; 95% CI 0.98 to 1.03) nor any secondary outcome. Analysis of both interventions combined showed a background trend of mixed improvement following feedback. CONCLUSIONS: There was no evidence that combined paper and digital feedback was more effective than digital-only feedback, despite the background of mixed improvements following both interventions. Challenges remain to understanding the barriers to influencing the prescribing of preventer inhalers and transitioning inhaler devices towards low-carbon 'green' alternatives; however, this study demonstrated the value of an efficient 'real-world' trial embedded within an existing quality improvement initiative. TRIAL REGISTRATION NUMBER: NCT05761873.
20 Apr 2026
Read appraisal →PloS one
Risk prediction for cardiovascular related diseases using PRS and EHR in the Framingham Heart Study
Cardiovascular disease is a leading cause of mortality and rising healthcare costs worldwide. Fortunately, the disease is preventable, and addressing risk factors can significantly reduce its effects. Over the past decade, risk prediction models have advanced significantly, with polygenic risk scoring analysis, which is often used in combination with clinical health information for prediction. However, most previous cardiovascular disease prediction studies based on polygenic risk scores have focused on a single specific disease or event, such as cardiac events. Given the complex nature of the cardiovascular disease, which involves a combination of genetic and environmental factors, a comprehensive analysis of the disease prediction results is essential. In this study, we investigate the genetic and environmental factors contributing to cardiovascular disease by utilizing data from the Framingham Heart Study, a leading cardiovascular cohort. We compared the prediction performance of different methods across various scenarios and assessed performance using various evaluation metrics to identify the best-fitting model for six cardiovascular related diseases. We also analyzed the feature importance of genetic and clinical variables, noting that different variables had varying effects on each disease. Our findings demonstrated the performance of prediction algorithms in forecasting cardiovascular disease by utilizing genetic and clinical factors, as well as highlighting the importance of each feature in the disease prediction. While models relying solely on polygenic risk score showed relatively low prediction performance for some diseases, integrating genetic information with clinical data improved prediction performance in most cases. For certain diseases, particularly those known to be heritable, polygenic risk scores demonstrated predictive ability, suggesting that they may serve as standalone predictive tools. We believe our study reveals the value of combining polygenic risk scores with clinical variables and expect that our thorough analysis can inform study designs tailored to specific diseases and research objectives.
20 Apr 2026
Read appraisal →PloS one
Impact of prophylactic oral azithromycin during labor on Azithromycin Resistance (AMR) in nasal Staphylococcus aureus and Streptococcus pneumoniae in women and infants in the multi-country Azithromycin Prevention in Labor Use Study (A-PLUS)
BACKGROUND: Prophylactic oral azithromycin vs. placebo reduced maternal, but not neonatal, mortality/sepsis in the A-PLUS Randomized Trial. While prophylactic intrapartum azithromycin reduces maternal mortality/sepsis, it may promote antimicrobial resistance (AMR) in commensal bacteria,. METHODS: Randomly selected women and their infants participating in A-PLUS were enrolled in a longitudinal cross-sectional sub-study to assess the presence of azithromycin resistance in selected bacteria in nasal cultures. Staphylococcus aureus and Streptococcus pneumoniae were cultured on selective agar, then azithromycin-containing agar to select for azithromycin resistant bacteria, identified biochemically. Azithromycin susceptibility was assessed by E-test. Nasal cultures were collected from women and infants between August 11, 2021 and September 18, 2023 during labor/day 1, day 7, 6 weeks, and 3, 6 and 12 months after delivery. RESULTS: The study enrolled 911 women and 915 liveborn infants at 8 sites in 7 countries. Azithromycin resistance in S aureus was higher and azithromycin susceptibility was lower in women receiving azithromycin compared with those receiving placebo on day 7 (P < 0.001), 6 weeks (P < 0.001) and 3 months (P = 0.009) after delivery. Azithromycin resistance in S aureus was also higher and azithromycin susceptibility was lower 6 weeks after delivery (P < 0.001) in infants born to women receiving azithromycin, Azithromycin resistance in S. pneumoniae was too sparse to interpret. CONCLUSIONS: There was an increase in prevalence of azithromycin resistance (or reduction in azithromycin susceptibility) in commensal nasal S. aureus between day 7, 6 weeks and 3 months in women exposed to azithromycin vs. placebo and only at 6 weeks in infants exposed to azithromycin vs. placebo. These differences between the azithromycin and placebo groups were no longer detected at 6 and 12 months post-partum in the women and after 6 weeks through 12 months in the infants.
20 Apr 2026
Read appraisal →PloS one
Uptake and determinants of immediate and extended postpartum long-acting reversible contraceptive use in Eastern and Western Africa: A systematic review and meta-analysis
BACKGROUND: Reducing unintended pregnancies and improving maternal/child health relies heavily on postpartum family planning (PPFP). Despite their high effectiveness, the use of long-acting reversible contraceptives (LARC), such as intrauterine contraceptive device (IUCD) and implants, is inconsistent in Africa after childbirth. This systematic review and meta-analysis aimed to assess the prevalence and determinants of immediate and extended postpartum use of long-acting reversible contraceptives in Eastern and Western Africa. METHODS: We searched PubMed, the Cochrane Library, Hinari, and gray literature sources (Google Scholar) for studies published between January 1, 2015, and December 12, 2025. Eligible studies reported LARC uptake within 12 months of postpartum. Heterogeneity was assessed using the I² statistic, publication bias using Egger's test, and study quality using the JBI 2020 checklist. Data were analyzed using Stata version 17 and R version 4.5. RESULTS: Sixty-eight studies were included, most of which were from Eastern Africa. The pooled prevalence was 21.7% for immediate postpartum LARC (IPP-LARC) and 19.5% for extended postpartum LARC (EPP-LARC). Uptake was significantly associated with counseling during maternal and child health visits, partner involvement, prior family planning use, and good knowledge. Age ≥ 35 years and higher education level also favored immediate postpartum IUD use. CONCLUSION: The uptake of postpartum LARCs remains low in Eastern and Western Africa. Strengthening FP counseling during MCH services, encouraging partner involvement, and improving knowledge are critical strategies to increase coverage and reduce unmet needs. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews (ID: CRD420250577642).
19 Apr 2026
Read appraisal →PloS one
Hybrid feature-selection and diversity-guided stacking framework for interpretable ensemble learning: Application to COVID-19 mortality prediction
BACKGROUND: Reliable predictive modeling in high-dimensional biomedical data requires a balance between accuracy, interpretability, and computational efficiency. However, existing ensemble methods often overlook model diversity or rely on ad hoc feature-selection approaches, which limit generalizability. This study introduces a hybrid feature-selection and diversity-guided stacking framework designed to improve robustness and scalability across clinical and other data-intensive domains. METHODS: The proposed framework integrates a hybrid feature-selection pipeline-combining Variance Inflation Factor (VIF), Analysis of Variance (ANOVA), Sequential Backward Elimination (SBE), and Lasso regression-to reduce multicollinearity and overfitting. It also employs a diversity-aware stacking strategy that constructs sub-model sets based on pairwise diversity measures (Disagreement, Yule's Q, and Cohen's Kappa) and non-pairwise metrics (Entropy and Kohavi-Wolpert). Sixteen base classifiers and five meta-learners were trained using repeated 10-fold cross-validation. The framework was evaluated using data from 4,778 hospitalized COVID-19 patients with 116 clinical and laboratory attributes, preprocessed using robust scaling and ROSE-based class balancing. RESULTS: The optimal configuration, which stacked Random Forest and XGBoost models using a Neural Network meta-learner, achieved 91.4% accuracy (95% CI: 89.8-92.8), AUC = 0.955, F1 = 0.801, and MCC = 0.746, outperforming the best individual model (AdaBoost, 90.2%). Training time (~450 s) and per-case inference time (<0.2 s) demonstrated computational feasibility. Feature-importance analysis and SHAP-based interpretation confirmed clinical relevance and interpretability. CONCLUSIONS: The hybrid feature-selection and diversity-guided stacking framework improves predictive accuracy and interpretability while maintaining computational efficiency. Although validated using COVID-19 mortality data, the approach is broadly applicable to biomedical, environmental, and engineering prediction tasks that require interpretable and scalable ensemble learning.
19 Apr 2026
Read appraisal →Journal of medical Internet research
Effectiveness of mHealth Interventions for Improving eHealth Literacy Among Patients With Chronic Diseases: Meta-Analysis and Systematic Review
BACKGROUND: With the widespread use of the internet and mobile devices, eHealth literacy promotion is critical for medical equity. Mobile health (mHealth) serves as a pivotal tool for enhancing eHealth literacy by providing accessible, interactive platforms for health information engagement. However, the evidence regarding the effectiveness of mHealth interventions on eHealth literacy among patients with chronic diseases remains inconclusive. OBJECTIVE: This study aimed to evaluate the effectiveness of mHealth interventions on eHealth literacy among patients with chronic diseases based on randomized controlled trials (RCTs) and summarize supportive evidence from quasi-experimental and qualitative studies. METHODS: A comprehensive search strategy was developed, and 8 electronic databases were systematically searched for studies published up to February 12, 2026. Patients with chronic diseases were included based on predefined inclusion criteria. The Cochrane risk of bias 2 tool for RCTs and the ROBINS-I tool for quasi-experimental studies were used to assess the risk of bias. Given the anticipated substantial heterogeneity among the studies included, we used a random-effects model based on the Hartung-Knapp-Sidik-Jonkman method to pool effect sizes. A narrative and quantitative synthesis of the findings was provided where appropriate. RESULTS: A total of 15 studies were included in this review, including 6 RCTs, 5 quasi-experimental studies, and 4 qualitative studies, involving a total of 2884 patients with chronic diseases. Meta-analyses of RCTs suggested that mHealth interventions could improve eHealth literacy, with a pooled mean effect size of standardized mean difference (SMD)=1. 19 (95% CI 0.14-2.23; P=.03; I²=97.75%; PI [prediction interval]=-2.68 to 5.05). Subgroup analyses by intervention targets showed that interventions on targets with specific disease produced larger mean effects (SMD=1.61; 95% CI 0.16-3.06; PI=-5.40 to 8.63), while interventions targeting the population with general chronic diseases produced smaller effects (SMD=0.36; 95% CI 0-0. 73; PI=-0. 21 to 0. 94). Analysis by intervention duration subgroup showed that the combined effect of studies with intervention duration <3 months was statistically significant (SMD=0.61; 95% CI 0.09-1.13; I²=88.04%; PI=-5.72 to 6.95); while the combined effect of studies with intervention duration ≥3 months was not statistically significant. Taking into account bias and the risk of GRADE (Grading of Recommendations, Assessment, Development, and Evaluation), the certainty of RCT evidence was moderate, and the certainty of quasi-experimental evidence was low. CONCLUSIONS: mHealth interventions could improve eHealth literacy among patients with chronic diseases on average. By using prediction intervals, this study reveals that the effectiveness of mHealth interventions is highly context-dependent and closely linked to implementation factors. Advancing beyond prior work, this study centers on eHealth literacy as a core outcome and integrates multiple types of evidence. Meanwhile, this finding emphasizes the need for evidence-based intervention programs and more rigorous implementation of intervention designs in future research.
19 Apr 2026
Read appraisal →Scientific reports
Food preferences and mortality risk in the prospective cohort of UK Biobank participants.
Food preferences may serve as less biased proxies for self-reported food intake in predicting health outcomes but have not yet been linked to mortality risk. We included 177,148 UK Biobank participants who completed a food preference questionnaire (FPQ), with a mean follow-up of 3.4 years (607,779 person-years; 3355 deaths). High versus low preference for 140 food items was tested using Cox regression with Holm adjustment. Sensitivity analyses excluded participants with key health conditions, additional supplement use, or short follow-up, added BMI and physical activity as covariates, and redefined preference groups. Higher preference for asparagus (hazard ratio (95% confidence interval)): 0.69 (0.62, 0.77)), aubergine (0.79 (0.72, 0.87)), black pepper (0.72 (0.64, 0.81)), broccoli (0.69 (0.61, 0.79)), butternut squash (0.75 (0.68, 0.83)), and extra virgin olive oil (0.67 (0.58, 0.78)) was linked to lower all-cause mortality, whereas higher preference for regular fizzy drinks (1.38 (1.24, 1.54)) was linked to higher mortality across all analyses. Specific food preferences are associated with all-cause mortality risk. FPQs may, therefore, complement conventional dietary assessments. Further studies should examine their associations with metabolic and cardiovascular outcomes.
19 Apr 2026
Read appraisal →Journal of health organization and management
Organisational professional support measures to enhance mental health and wellbeing in female healthcare workers: an umbrella review
PURPOSE: This study aims to synthesise evidence on organisational professional support measures that enhance female healthcare workers' mental health and wellbeing. Female healthcare workers face high rates of mental health challenges, impacting their ability to provide optimal care. DESIGN/METHODOLOGY/APPROACH: This umbrella review adhered to the nine-step pathway to conducting umbrella reviews by Cant et al. (2022) and reported following the Preferred Reporting Items for Overview of Reviews checklist (Pollock, 2019). A search of Embase, Medline, CINAHL via EBSCO and the Cochrane Library for English language papers from January 2011 onwards was conducted (search date: February 2024). Following an identification of relevant papers and data extraction, themes were developed using a narrative synthesis approach. FINDINGS: In total, 32 systematic reviews met the inclusion criteria. From the data synthesis, four themes were developed, namely lack of studies specific to female healthcare workers, diversity and variability of interventions, interventions best related to staff outcomes versus organisational outcomes and social connections at work can be supportive or stressful. ORIGINALITY/VALUE: Evidence supports that person-directed interventions including cognitive-behavioural therapy and relaxation measures may enhance staff-level outcomes. In contrast, organisation-directed interventions such as clinical supervision and mentoring, or a combination of person- and organisation-centred interventions, appear to enhance both staff and organisational outcomes. Limitations in existing studies highlight the need for improved research conduct and reporting.
18 Apr 2026
Read appraisal →JMIR aging
"Living Inside the Walls": Systematic Review and Qualitative Meta-Synthesis
BACKGROUND: Social isolation is a prevalent issue among older people in long-term care facilities (LTCFs), with profound negative impacts on their quality of life and mental health. However, the authentic experiences and underlying mechanisms of social isolation among older people in LTCFs remain understudied. A nuanced understanding of these experiences is essential for designing targeted nursing interventions. OBJECTIVE: This study aimed to systematically review and synthesize qualitative evidence to explore the experiences of social isolation among older adults in LTCFs and analyze them in terms of causes, mechanisms, outcomes, and strategies. METHODS: A systematic review and qualitative meta-synthesis were conducted. We searched PubMed, Web of Science, Embase, PsycInfo, Cochrane Library, CINAHL, Scopus, Chinese Biomedical Literature Database, CNKI, Wanfang Data, and Weipu (VIP) with no restriction on the start year, up to February 2025. Two reviewers (WL and ZM) independently screened studies, extracted data using a Microsoft Excel spreadsheet, and assessed study quality with the Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research. Qualitative data synthesis was performed following Thomas and Harden's thematic and content analysis method, including line-by-line coding of participant quotes, organizing codes into descriptive themes, and developing analytical themes. RESULTS: A total of 4856 papers were retrieved through systematic searches, and 14 qualitative studies met the inclusion criteria. Four overarching analytical themes were identified: (1) root cause: person-environment mismatch (encompassing 4 interrelated dimensions: imbalance between declining individual capacity and insufficient environmental support, negative self-perception paired with inadequate positive environmental feedback, personal biases conflicting with homogeneous institutional social ecology, and disrupted social roles due to rigid institutional management); (2) overt behavioral patterns: proactive isolation, defensive isolation, and adaptive isolation; (3) inner emotional experiences: feelings of confinement, sorrow, and weariness; and (4) strategies for restoring person-environment match: active engagement in interaction, rational acceptance of coexistence, and passive avoidance and withdrawal. Notably, person-environment mismatch was confirmed as the core mechanism driving the onset and persistence of social isolation in this population. CONCLUSIONS: Person-environment mismatch is the fundamental driver of social isolation among older adults in LTCFs. Interventions should prioritize restoring person-environment alignment-including optimizing physical environments, reconstructing supportive social environments, and enhancing psychological empowerment. Future studies should focus on developing tools to quantify person-environment matching degrees in LTCFs and conduct longitudinal evaluations of targeted interventions to further reduce social isolation and promote active social participation among older people.
18 Apr 2026
Read appraisal →Hernia : the journal of hernias and abdominal wall surgery
The impact of socioeconomic status in hernia treatment: a qualitative systematic review.
INTRODUCTION: Hernias are among the most common surgical conditions worldwide. However, access to optimal treatment remains disproportionately distributed. Socioeconomic disparities play a critical role in determining whether patients receive timely surgical intervention, access to minimally invasive techniques, or suffer from postoperative complications due to delayed or suboptimal care. This study aims to evaluate the impact of socioeconomic disparities on the treatment of ventral hernia repair. METHODS: This systematic review was conducted following PRISMA guidelines. A comprehensive search was conducted using MEDLINE/Pubmed, EMBASE, Web of Science, Cochrane Library, and LILACS, from inception until March 2026 without any filter applied. A search strategy was created using the MeSH terms. Our inclusion criteria comprise studies related to socioeconomic disparities in ventral hernia repair within the United States. Due to heterogeneity in study designs, socioeconomic variables, and outcome definitions, a meta-analysis was not feasible, and findings were synthesized using a narrative synthesis. A qualitative assessment of included studies was made using the Cochrane Risk of Bias tool, ROBINS-I. RESULTS: A total of 28 studies were included, encompassing 2,096,513 patients with ventral hernia. Most were retrospective cohorts, with sample sizes ranging from a few hundred to over 665,000 patients. Across studies, patients with government funded insurance (Medicaid or Medicare) generally experienced higher rates of complications, readmissions, and recurrences compared to commercial insured patients, although the magnitude of association varied. Odds ratios demonstrated increased risks of wound complications, readmission, and recurrence among government funded insured and uninsured patients, while commercial insured and higher-income patients were more likely to undergo advanced surgical approaches and had shorter hospital length of stay. Some studies also highlighted socioeconomic and racial disparities, with vulnerable populations and minority groups showing disproportionately higher complication rates and different patterns of insurance coverage. CONCLUSION: This systematic study demonstrates significant racial and socioeconomic disparities in ventral hernia repair. Government funded insurance holders or lower incomers, faced higher complication rates, more emergent presentations, and worse outcomes, including increased mortality and readmissions. Moreover, they usually have less access to minimally invasive and robotic techniques. These inequities highlight systemic barriers in healthcare access.
18 Apr 2026
Read appraisal →JMIR formative research
Public Perceptions of AI in Medicine and Implications for Future Medical Education: Cross-Sectional Survey
BACKGROUND: The integration of artificial intelligence (AI) into clinical practice is contingent on public trust. This trust often depends on physician oversight, yet a significant gap exists between the need for AI-competent physicians and the current state of medical education. While the perspectives of students and experts on this gap are known, the views of the US general public remain largely unquantified. OBJECTIVE: This study aimed to assess US public perceptions regarding AI in medicine and the corresponding emergent needs for medical education. We specifically sought to quantify public trust in different diagnostic scenarios, concerns about physician overreliance on AI, support for mandatory AI education, and priorities for the future focus of medical training. METHODS: We conducted a cross-sectional, web-based survey of adults in the United States in November 2025. Participants (N=524) were recruited via SurveyMonkey Audience. We calculated descriptive statistics, frequencies, proportions (percentages), and 95% CIs for all main survey items. RESULTS: A total of 524 participants completed the survey. Most (n=329, 62.8%; 95% CI 58.6%-66.9%) placed the most trust in a physician's diagnosis based on their expertise alone; only 7.8% (n=41; 95% CI 5.5%-10.1%) trusted an AI-first diagnostic model. Trust was highly contingent on training: 93.9% (n=492) of participants rated formal physician training on AI limitations as "essential" or "very important." Widespread concern about physician overreliance on AI was reported, with 81.1% (n=425) being "very concerned" or "extremely concerned." Consequently, 85.1% (n=446) agreed or strongly agreed that training on AI use, ethics, and limitations should be mandatory in medical school. When asked about future educational priorities, 70.2% (n=368; 95% CI 66.3%-74.1%) believed that medical education should focus on human-centered skills (eg, empathy and communication) over clinical skills. CONCLUSIONS: The US public expressed conditional trust in medical AI, strongly preferring physician-led and critically supervised models. These findings reveal a clear public mandate for medical education reform. The public expects future physicians to be mandatorily trained to appraise AI, understand its limitations, and refocus their professional development on the human-centered skills that technology cannot replace.
18 Apr 2026
Read appraisal →Journal of global health
National, regional and provincial prevalence of peripheral artery disease in Chinese adults in 2023: an updated systematic review and modelling study
BACKGROUND: Peripheral artery disease (PAD), a common atherosclerotic condition characterised by the narrowing or obstruction of peripheral arteries, has become a substantial public health concern in China. However, its prevalence across the country at the provincial level has never been quantified. Through an updated systematic review and modelling study, we aimed to estimate the national, regional, and provincial prevalence of PAD among Chinese individuals aged 30-89 years in 2023. METHODS: We conducted an updated literature search in PubMed, Embase, MEDLINE, the China National Knowledge Infrastructure, Wanfang, and the Chinese Science and Technology Journal Database to identify studies published between 4 March 2017 and 12 August 2024 reporting on the prevalence of PAD in the general Chinese population. We also identified and included studies from previous systematic reviews. We then used a multilevel mixed-effects meta-regression model to generate the age- and sex-specific prevalence estimates of PAD among individuals aged 30-89 years at the national level. We calculated pooled odds ratios (ORs) for factors associated with PAD using a random-effects meta-analysis and incorporated them into an 'associated factor-based model' to estimate regional and provincial prevalence. RESULTS: We included 54 articles from all searches. Model-based estimates indicated that the overall prevalence of PAD among Chinese adults aged 30-89 years in 2023 was 5.47% (95% confidence interval (CI) = 4.64-6.44), equivalent to 49.90 million (95% CI = 42.32-58.73) affected individuals. Prevalence increased progressively with age, ranging from 4.23% (95% CI = 3.58-5.00) among individuals aged 30-34 years to 18.37% (95% CI = 15.90-21.13) among those aged 85-89 years. The overall prevalence was higher in females (6.19%; 95% CI = 5.25-7.27) than males (4.76%; 95% CI = 4.03-5.61). Regionally, Northeast China had the highest prevalence of PAD at 5.87% (95% CI = 4.98-6.91), while Central China had the lowest at 5.26% (95% CI = 4.46-6.19). At the provincial level, the prevalence of PAD was the highest in Beijing (6.40%; 95% CI = 5.43-7.53) and lowest in Tibet (4.35%; 95% CI = 3.68-5.12). Female sex, current smoking, hypertension, diabetes, coronary heart disease, and stroke were identified as factors significantly associated with PAD. CONCLUSIONS: We found that PAD is prevalent in China, with pronounced age-related trends, sex differences, and regional disparities. These findings could inform targeted public health initiatives and appropriate resource allocation. REGISTRATION: PROSPERO: CRD420251118923.
18 Apr 2026
Read appraisal →PloS one
Mukara: A deep learning alternative to the four-step travel demand model with a case study on interurban highway traffic prediction in the UK.
Accurate traffic volume prediction is essential for managing congestion, improving road safety, mitigating environmental impacts, and supporting long-term transportation planning. The traditional four-step travel demand model (FSM) is a well-established framework, but it relies on static survey data, substantial calibration effort, and simplified behavioural assumptions that may not adequately capture complex travel patterns. In contrast, data-driven models are capable of learning nonlinear relationships from large datasets, yet they are often designed for short-term forecasting and typically do not target the long-term, segment-level volume estimation tasks required for strategic planning. This study proposes Mukara, a deep learning framework that directly approximates the mapping from external socioeconomic and network features to observed traffic volumes on highway trunk road segments. The model is trained on eight years of data from England and Wales and incorporates population, employment, land use, road network characteristics, and points of interest as inputs. Mukara achieves a mean GEH of 50.74, a mean absolute error of 8,989 vehicles per day, and an R2 of 0.583 under random cross-validation, outperforming baseline models and existing studies under comparable settings. Under a more stringent region-based spatial cross-validation scheme, performance remains robust, demonstrating strong spatial transferability. Ablation experiments further demonstrate the robustness of the proposed architecture and reveal the relative importance of different input feature groups for prediction.
17 Apr 2026
Read appraisal →PloS one
upsML: A high-accuracy machine learning classifier for predicting Plasmodium falciparum var gene upstream groups
Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1), encoded by the hypervariable var gene family, is central to malaria pathogenesis, influencing both disease severity and immune evasion. Classifying var genes into upstream groups (upsA, upsB, upsC, upsE) is important for understanding parasite biology and clinical outcomes, but remains challenging, especially with partial sequences, such as the DBLα tag or RNA-Seq assemblies. We developed upsML, a machine-learning-based classifier trained on 2,530 curated var genes, to accurately assign upstream groups based on sequence features from different partial gene regions. We compared seven methods, including support vector machines, random forests, XGBoost, and HMMER models. Several models in upsML achieve accuracies of 83% for DBLα-tag sequences and 92% for full-length PfEMP1 sequences, thereby significantly outperforming existing tools. Additionally, we developed a model to distinguish internal from subtelomeric var genes, which we applied to a global collection of P. falciparum genomes, revealing a higher frequency of internal var genes in Asia. upsML is available at https://github.com/sii-scRNA-Seq/upsML, providing a robust and efficient resource for large-scale var gene analysis. It can classify var genes from 20 genomes in under one second.
17 Apr 2026
Read appraisal →JMIR formative research
A Survey of Primary Care Clinician Experiences With Electronic Health Record-Based Clinical Decision Support to Improve HIV Pre-Exposure Prophylaxis Prescribing
A survey of primary care clinicians suggests that a clinical decision support tool to support sexual risk assessment and prescribing of HIV pre-exposure prophylaxis was appropriate and useful for identifying at-risk patients, but uptake was hindered by workflow and usability barriers, which underscores the importance of postimplementation clinician feedback to improve the use of clinical decision support tools.
17 Apr 2026
Read appraisal →Journal of global health
The impact of disasters on maternal mental health: a systematic review
BACKGROUND: The vulnerability of maternal mental health is increasing with the frequent increase in natural and man-made disasters, yet evidence remains fragmented. We aimed to synthesise quantitative evidence on the impact of disaster exposure on maternal mental health and related pregnancy outcomes. METHODS: We systematically searched 12 electronic databases, nine sub-databases, and additional web sources for the studies published between 1995 and 2025. We included studies that assessed the impact of disaster exposure during pregnancy and provided quantitative outcomes for depression, anxiety, stress, posttraumatic stress disorder (PTSD), or adverse pregnancy outcomes. RESULTS: Of 18 604 studies, 24 studies met the inclusion criteria. Natural disasters were the highest group (n = 16), including earthquakes (n = 8), floods/cyclone/hurricane (n = 7), and wildfire (n = 1), followed by man-made disaster (n = 7), including conflict/war/terrorism (n = 5), nuclear disaster (n = 1), plane crash (n = 1), and war (n = 1), and one hybrid disaster. Disaster showed a consistent increase in the risk of depression, anxiety, stress, and PTSD among pregnant women, with effects persisting up to six years post-disaster event. Across studies, disaster exposure increased maternal mental health problems by approximately 30% to over 200%, and PTSD odds increased seven to 10-fold among highly exposed pregnant women. Three studies reported that both depression and PTSD during pregnancy were associated with adverse pregnancy or early child outcomes, suggesting potential intergenerational effects. CONCLUSIONS: Disasters exert enduring and profound impacts on maternal mental health, with consequences cascading across both mother and child. Urgent, cost-effective and disaster-informed policies are needed to mitigate such long-term impacts. REGISTRATION: PROSPERO: CRD42023445559.
17 Apr 2026
Read appraisal →Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Crowdsourced versus large language models forecasting: evidence for the accuracy-correlation effect
Over the past quarter century, crowdsourced forecasting has largely outperformed individual forecasters. Today, large language models (LLMs), aggregating human knowledge at scale, constitute a new form of collective intelligence (CI). A central question is how LLM predictive accuracy associates with human-AI correlation, and whether this relationship exceeds what would be expected if both merely track the same underlying truth. We investigate this through the accuracy-correlation effect (ACE), which posits that as algorithmic systems improve, they increasingly correlate with human predictions, potentially diminishing human value in hybrid ensembles. Using 76 model × prompt forecast sets from 16 LLMs on 580 resolved ForecastBench questions, we computed LLM accuracy and correlations with two human aggregates (superforecasters, general public), separately for databases (n = 526) and prediction markets (n = 54) questions. Linear mixed-effects models show a robust positive association between LLM accuracy and human-AI correlation that substantially exceeds independent-errors predictions. Correlations were lower for superforecasters than for the general public, and weaker for markets than for data questions. These results support ACE while indicating that increasing correlation reflects more than improved signal tracking alone, suggesting that simultaneous increases in accuracy and correlation may reduce optimal human weights in data-rich settings, while human judgement retains critical value in contextual reasoning scenarios. This article is part of the theme issue 'The evolution of collective intelligence'.
17 Apr 2026
Read appraisal →African journal of reproductive health
Mapping research fronts of reproductive medicine using the NHANES database: A bibliometric and thematic analysis
Reproductive health, infertility, and perinatal diseases significantly challenge human health development and continuity, requiring multidisciplinary approaches for enhanced academic understanding and practical solutions. This study used bibliometric analysis to examine related articles in the web of science (WoS) database, employing tools including bibliometrix and VOSviewer for systematic literature analysis. To capture the broader context of high-impact research, we first analyzed 1,026 highly-cited and hot papers in reproductive medicine, which revealed evolving thematic trends and global collaboration patterns. Then we examined 232 literatures using NHANES datasets for reproductive health research to identify research gaps and opportunities for further research in this field. The analysis revealed key trends, areas of concentration, and potential knowledge gaps in the literature, while the thematic analysis of reproductive health studies utilizing the NHANES database further underscored the wealth of data amenable to multidisciplinary investigation. Future research directions to explore new dimensions of reproductive health, improving health policies and clinical practices in this field using NHANES database are also suggested. The study concludes that multidisciplinary research using comprehensive datasets like NHANES is crucial for advancing understanding of reproductive health, infertility, and perinatal outcomes. La santé reproductive, l'infertilité et les maladies périnatales constituent un défi majeur pour le développement et la continuité de la santé humaine, nécessitant des approches multidisciplinaires afin d'améliorer la compréhension académique et de proposer des solutions pratiques. Cette étude a utilisé une analyse bibliométrique pour examiner les articles pertinents dans la base de données WoS, en employant des outils tels que Bibliometrix et VOSviewer pour une analyse systématique de la littérature. Afin de saisir le contexte plus large de la recherche à fort impact, nous avons d'abord analysé 1 026 articles hautement cités et à tendance chaude en médecine reproductive, ce qui a révélé les tendances thématiques évolutives et les modèles de collaboration internationale. Nous avons ensuite examiné 232 publications utilisant les jeux de données NHANES pour la recherche sur la santé reproductive, afin d'identifier les lacunes de recherche et les opportunités pour de futures études dans ce domaine. L'analyse a mis en évidence les tendances clés, les domaines de concentration et les lacunes de connaissances potentielles dans la littérature, tandis que l'analyse thématique des études sur la santé reproductive utilisant les jeux de données NHANES a en outre souligné la richesse des données susceptibles d'être étudiées de manière multidisciplinaire. Les orientations futures de la recherche visant à explorer de nouvelles dimensions de la santé reproductive, à améliorer les politiques sanitaires et les pratiques cliniques dans ce domaine à l'aide des jeux de données NHANES sont également proposées. L'étude conclut que la recherche multidisciplinaire utilisant des jeux de données complets tels que NHANES est cruciale pour faire progresser la compréhension de la santé reproductive, de l'infertilité et des issues périnatales.
17 Apr 2026
Read appraisal →Food chemistry
Machine learning-driven flavoromics: Decoding stage-specific volatile compound dynamics and sensory deterioration in stored infant formula
Infant formula (IF) is a vital nutritional source for infants. However, its sensory quality deteriorates during prolonged storage, impacting consumer acceptance. This study investigated the stage-specific sensory deterioration mechanisms and the predictive modeling of IFs during storage by integrating flavoromics, fatty acid dynamics, and machine learning. Quantitative descriptive analysis identified six key attributes driving quality loss, with one-stage IF showing the earliest and most pronounced decline. Volatile compound profiling revealed aldehydes (hexanal, octanal) and ketones as dominant off-flavor markers, correlating with lipid oxidation pathways. Fatty acid analysis showed the degradation of polyunsaturated fatty acids, particularly linoleic and α-linolenic acid, as key drivers of off-flavor generation. Using only six lipid-oxidation-derived volatiles, Random Forest and XGBoost models accurately predicted stage-specific sensory scores (with R2 > 0.85), directly linking fatty acid oxidation to flavor deterioration. This work establishes lipid oxidation as predominant degradation mechanism and provides practical, data-driven tool for shelf-life optimization.
17 Apr 2026
Read appraisal →Computers in biology and medicine
A systematic review and benchmarking of modern metagenomic tools for taxonomic classification
Advancements in metagenomics have been driven by the continuous development of bioinformatic tools, particularly taxonomic classification software, which are central to the accurate characterization of microbial communities. However, establishing direct comparisons between these tools remains challenging due to variations in evaluation metrics, reference databases, and input data types. In this study, we present a systematic review of recently developed metagenomic taxonomic classification tools. Of the 31 identified tools, nine satisfied all functional and methodological criteria for the benchmark analysis. We evaluated their accuracy and computational performance using a standardized dataset derived from the NCBI RefSeq database. Our analysis revealed that most of these tools are domain-specific, each excelling in particular areas. Tools like TAMA, CAMITAX and PhyloFlash achieved higher accuracy for prokaryotic organisms, while ViWrap and PhaBOX achieved higher accuracy for viral classifications. SqueezeMeta achieved high F1 scores across most domains, though its assembly-based architecture limits effectiveness on highly diverse samples. MegaPath-Nano was least affected by increased mutation rates. The execution time varied widely among the tools, with domain-specific and machine learning-based tools generally being faster, while tools like BASTA had longer runtimes and lower accuracy. This review synthesizes performance results for current tools, providing an overview of their strengths and computational methodologies.
17 Apr 2026
Read appraisal →JMIR human factors
Comparing Images of Depression in Mass Media and AI-Generated Pictures: Mixed Methods Study
BACKGROUND: Images play an important role in reducing stigma related to mental health, which often is distorted in the media. In recent years, generative artificial intelligence (AI) has been used to generate images related to mental health. However, first reports suggest that AI-generated images do not depict mental health conditions accurately. In-depth studies on the topic of mental health representations in AI-generated images are still missing. OBJECTIVE: The main objective of this study is to analyze and compare the visual representation of depression in mass media and in AI-generated images. METHODS: The methodologies used were discussion groups (15 participants) and a quasi-experimental online survey (792 interviewees), aimed at people with depression and young people. RESULTS: The results showed that both the images used in the media and those generated by AI reproduced stereotypes and stigmas about depression. However, participants considered AI-generated pictures to be more stereotypical, stigmatizing, and more likely to have a negative impact on people with depression. In contrast, media images were considered more appropriate, realistic, inclusive, and that better reflected the relationship between gender and depression. Statistically significant differences were observed between the control and test groups in both people with depression and young people (P<.001), indicating that when people were aware of what images were AI-generated, they tended to reject them to a greater extent. CONCLUSIONS: Considering the current trend toward the widespread use of AI in mental health communication, it is crucial to promote closer collaborations between science journalists, AI developers, and mental health experts, including patients' associations, as well as a shift toward user-participatory AI design.
17 Apr 2026
Read appraisal →BMJ open
Trends and characteristics of syphilis incidence in Japan: a nationwide claims-based analysis of working-age populations and their dependents, 2016-2023
OBJECTIVES: To examine trends and demographic characteristics of syphilis incidence in Japan using a large nationwide claims database with family linkage, with particular focus on differences by sex, age, HIV status and family relationships. DESIGN: Retrospective cohort study. SETTING: JMDC claims database (JMDC Inc, Tokyo, Japan), a nationwide administrative claims database in Japan, using data from 2016 to 2023. PARTICIPANTS: Individuals aged 16-59 years enrolled in the JMDC database, including employees of medium-to-large companies and their dependents (n=12.5 million). OUTCOME MEASURES: Syphilis cases were defined by International Classification of Diseases, 10th Revision (ICD-10) codes (A50-A53) with concurrent treatment with relevant antibiotics. We determined syphilis incidence rates per 100 000 person-years, stratified by sex, age, HIV status and family relationships. We also investigated within-couple concordance patterns and reinfection rates. RESULTS: Among 16.4 million individuals, 9357 syphilis infections were identified among 8881 individuals. Incidence increased markedly during the pandemic, reaching 48.2 (men) and 12.9 (women) per 100 000 person-years in 2023. Men showed consistently high incidence in their 20s-50s, whereas female incidence peaked in the 10s-20s. Among 2 294 184 married couples, dependent women (ie, housewives) showed comparably high incidence to age-matched men (10-20 per 100 000 person-years). In 1286 couples with at least one syphilis case, 12.4% of wives in their 20s were also diagnosed, compared with 2%-3% in older groups. In 20s couples, the proportion of syphilis among wives only and husbands only was similar. Subgroup analysis revealed notably high incidence among unmarried female dependent youths (2022: 66.7 per 100 000 person-years). Individuals living with HIV had substantially elevated incidence (3000-15 000 per 100 000 person-years) and reinfection rates. CONCLUSIONS: Using a large claims database with family linkage, we found that while male syphilis incidence remained dominant, high rates were also observed among dependent women and youths. These findings suggest that syphilis risk may extend beyond traditionally recognised high-risk populations and emphasise the need for targeted screening and preventive strategies in broader demographic groups.
17 Apr 2026
Read appraisal →BMJ open
mHealth-based Healthy Lifestyle Promotion (MYLIFE) for metabolic syndrome risk reduction in Chinese employed adults: protocol for a cluster-randomised controlled trial
INTRODUCTION: Metabolic syndrome (MetS) poses a significant public health challenge among employed adults. Lifestyle modifications have been shown to be effective in preventing the onset and progression of MetS in employed adults, and the widespread adoption of mobile and wearable technologies introduces an appealing approach to mHealth lifestyle interventions. When widely implementing smartphone-based interventions for employed adults, enhancing equitable access and promoting wearable device use for those with MetS is a more cost-effective way to reduce health disparities, particularly in resource-limited settings. However, relevant evidence is currently lacking. OBJECTIVE: This study aims to design an mHealth-based Healthy Lifestyle Promotion (MYLIFE) trial, a three-arm randomised controlled trial (RCT), to evaluate the effectiveness of a smartphone-based lifestyle intervention and a combined smartphone-based lifestyle intervention with intensive intervention for MetS individuals using wearable devices, in reducing MetS risk among employed adults. METHODS AND ANALYSIS: This is a three-arm, parallel, single-blind, cluster RCT with a 12-week intervention and a total follow-up of 1 year. The trial will recruit 120 workplaces from the Chinese Cohort of Working Adults in a 1:1:1 ratio to either a control group or one of two intervention groups. Within these workplaces, a total of at least 348 eligible participants will be enrolled. The regular mHealth group will receive smartphone-based intervention. The intensive mHealth group will receive smartphone-based intervention for all participants, and an additional wearable device-intensive intervention for those with MetS. The primary outcome is the Chinese MetS Z score at 12 weeks. Secondary outcomes include MetS Z score, prevalence of MetS, specific MetS components, questionnaire-based indicators, and clinical outcomes at 12 weeks and 1 years. The main analysis will follow the intention-to-treat principle, using mixed-effects models to assess between-group differences in outcomes. ETHICS AND DISSEMINATION: The protocol has been approved by the Ethics Committee of the West China School of Public Health and the West China Fourth Hospital, Sichuan University (Gwll2025024). The findings will be published in peer-reviewed journals and presented at scientific conferences. TRIAL REGISTRATION NUMBER: ChiCTR2500101904.
17 Apr 2026
Read appraisal →BMJ open
Association between ambient air pollution exposure levels and the risk of developing pulmonary embolism in the Chinese population: findings from the Chinese Cardiovascular Association (CCA) Database-Chest Pain Centre
OBJECTIVE: To analyse the associations between exposure to different air pollutants and the morbidity of pulmonary embolism (PE). DESIGN: Time series study with a distribution lag non-linear model. SETTING: 275 cities in China, 1 January 2015 to 31 March 2022. PARTICIPANTS: 27 369 cases of PE. MAIN OUTCOME MEASURES: The associations between exposure to different air pollutants and the morbidity of PE. RESULTS: During the study period, 27 369 cases of PE were recorded. PM2.5(Particulate Matter 2.5), PM10(Particulate Matter 10) and NO2(Nitrogen Dioxide) exposure levels were associated with an increased risk of developing PE in the single-pollutant model. PM2.5 exposure caused the greatest risk of developing PE at lag 1 in the single-day lag model, with a relative risk (RR) value of 1.033 (95% CI 1.007 to 1.058). PM10 and NO2 exposure had the greatest effects at lag 0, with RR values of 1.038 (95% CI 1.016 to 1.059) and 1.039 (95% CI 1.009 to 1.068), respectively. No associations were found between CO(Carbon Monoxide), O3(Ozone) or SO2(Sulfur Dioxide) exposure levels and the risk of developing PE. PM2.5, PM10 and NO2 exposure levels were most strongly associated with the development of PE at lag 01 in the cumulative lag model, with RR values of 1.052 (95% CI 1.009 to 1.095), 1.053 (95% CI 1.020 to 1.086) and 1.058 (95% CI 1.005 to 1.111), respectively. CONCLUSIONS: Short-term exposure to PM2.5, PM10 and NO2 can increase the risk of developing PE, especially in females. The effects of PM2.5 and PM10 exposure were more significant in cold seasons and in North China.
17 Apr 2026
Read appraisal →Infection and immunity
Maternal influences on oral microbiome development and implications for early childhood health: a systematic review
A deeper understanding of how maternal-infant interactions shape the establishment and diversification of the oral microbiome could have significant clinical applications; however, relatively few studies emphasize early maternal-infant microbial connections. This systematic review provides a longitudinal analysis of oral microbiome development from birth to five years, focusing on the relationship between maternal and infant microbiomes. We conducted a systematic search (June 2025) using keywords "mother," "children," "oral microbiome," and "longitudinal" across PubMed, Cochrane Library, and Embase. Twelve studies fulfilled the inclusion criteria: longitudinal design, healthy mother-child dyads, saliva sample collection, and relevant age range. We excluded review articles, non-English publications, and studies with overlapping data. Results were synthesized by developmental stage and topic. Overall, current literature agrees that the mother is an important source of exposure for initial colonization of the newborn's oral microbiome. Several studies indicated that the oral microbiome at birth is diverse and unspecialized, composed mostly of maternally derived strains. Rapid selection occurs over the first few weeks, as the relative abundances of typical oral bacterial species increase. Throughout the first year, increases in diversity strengthen the resemblance between infant and maternal microbiomes. The microbiome appears to stabilize around 3-5 years. In conclusion, maternal-infant connections play a significant role in influencing oral microbiome development during the first 5 years of life. This review highlights the need for future studies to incorporate larger, longitudinal designs with metadata and advanced tools to clarify the roles of delivery mode, tooth eruption, and parental lifestyle habits in shaping early oral microbiome development.
17 Apr 2026
Read appraisal →JMIR mental health
Determinants of Digital Health Literacy Among Patients With Serious Mental Illness: Cross-Sectional Survey
BACKGROUND: Individuals with serious mental illness increasingly use digital devices and the internet to access health information and services but often face challenges when navigating digital tools, which may limit the benefits they receive from online health resources and digital health care services. OBJECTIVE: The objective of our study was to assess digital health literacy among individuals with serious mental illness and identify factors influencing this literacy. METHODS: Participants were recruited, using convenience sampling, from 2 psychiatric clinics, 1 day-care center, and 4 halfway houses in Taipei, Taiwan, between May 2024 and February 2025. Self-reported data were collected using a survey that incorporated the eHealth Literacy Scale, the Attitudes Toward Computer/Internet Questionnaire, and the Mobile Device Proficiency Questionnaire. Generalized linear modeling was applied to identify factors associated with digital health literacy. RESULTS: Among 255 participants included in the analysis, 83.5% (n=213) reported owning at least 1 digital device. Digital health literacy was significantly lower among individuals who reported greater perceived difficulty in using digital tools (B=-1.533, 95% CI -2.350 to -0.717; P<.001) and higher distrust in online information (B=-0.986, 95% CI -1.916 to -0.056; P=.04). By contrast, greater mobile device proficiency (B=0.144, 95% CI 0.008-0.281; P=.04) and self-efficacy (B=1.777, 95% CI 0.376-3.177; P=.01) were positively associated with digital health literacy. CONCLUSIONS: Despite widespread device ownership, digital health literacy was varied and generally suboptimal among patients with serious mental illness. Perceived difficulty and distrust emerged as major barriers; proficiency and self-efficacy facilitated higher literacy. These findings highlight the need for mental health professionals to integrate tailored digital skills training, confidence-building strategies, and ongoing support into digital health interventions for individuals with serious mental illnesses.
16 Apr 2026
Read appraisal →Global health action
Impact of climate change on pediatric health outcomes
Climate change has become one of the most critical health issues globally in the twenty-first century with children bearing the disproportionate burden of the burden since they are more vulnerable than adults because of their physiological, behavioral, and developmental capacities. It is a systematic review that rates the evidence of the relationship between climatic exposures such as heat, air-pollution, and extreme weather events and pediatric health outcomes. The number of peer-reviewed studies involved was 23 published in 2000-2025, which represented different geographic areas and study designs and assessed acute and chronic health outcomes. The Newcastle-Ottawa Scale and the ROBINS-I tool were used to evaluate the methodological quality, and the majority of the studies had low to moderate risks of bias. The narrative synthesis shows that there are always links between air pollutants especially PM2.5, NO2 and O3 and respiratory morbidity, prevalence of asthma and hospitalization of children. Amplified temperatures as well as heat waves were associated with increased cases of heat illness, dehydration, and febrile state in infants and young children. There were elevated cases of diarrheal and vector-related infections, especially in low-resource settings, which were linked to extreme weather events especially floods. Although the overall results were similar, significant differences in the regions and methods were found, and low-income countries show little evidence. In addition, exposures as analyzed in most studies were usually considered individually, which may have underestimated the cumulative or compound climate risks. Main findings: This review shows that rising temperatures, air pollutants, and extreme weather events are consistently linked with higher rates of respiratory illness, heat-related illness, and infectious diseases among children.Added knowledge: The synthesis brings together two decades of evidence showing that children across multiple continents experience similar health vulnerabilities when exposed to climate-related environmental conditions.Global health impact for policy and action: The findings highlight an urgent need for stronger climate-responsive child health policies and early warning systems to protect children from worsening environmental threats worldwide.
16 Apr 2026
Read appraisal →JMIR formative research
Designing Psychologically Grounded Artificial Intelligence for Supporting Bystander-Based Cyberaggression Intervention: Mixed Methods Exploratory Study
BACKGROUND: Cyberaggression poses a growing threat to mental health, contributing to increased distress, reduced self-esteem, and other adverse psychosocial outcomes. Although bystander intervention can mitigate the escalation and impact of cyberaggression, individuals often lack the confidence, strategies, or language to respond effectively in these high-stakes online interactions. Advances in generative artificial intelligence (AI) present a novel opportunity to facilitate digital behavior change by assisting bystanders with contextually appropriate, theory-informed intervention messages that promote safer online environments and support mental well-being. OBJECTIVE: This mixed methods design study aimed to explore the feasibility of using generative AI to support bystander intervention in cyberaggression on social media. Specifically, we examined whether AI can generate effective responses aligned with established intervention strategies and how these responses are perceived in terms of their potential to de-escalate online harm and foster behavior change. METHODS: We collected 1000 real-world cyberaggression examples from public social media datasets and generated bystander intervention responses using 3 distinct prompt strategies: a generic policy reminder, a baseline GPT prompt, and a theory-driven GPT prompt (AllyGPT). To evaluate the responses, we conducted computational linguistic analyses to assess their psycholinguistic features and carried out a mixed methods evaluation. Three trained coders rated each message on favorability, conversational impact, and potential to change behavior and later participated in semistructured interviews to reflect on their evaluation process and perceptions of intervention effectiveness. RESULTS: Linguistic analyses revealed that baseline GPT responses exhibited more emotionally positive and authentic language compared to AllyGPT responses, which showed a more analytical and assertive tone. Policy reminder messages were linguistically rigid and lacked emotional nuance. Human evaluation results showed that AllyGPT responses received the highest effectiveness ratings for low-incivil cyberaggression cases in 2 dimensions (favorability and changing behavior), and baseline GPT works better for mid and high levels for all effectiveness dimensions. For medium- and high-incivility aggressions, baseline GPT responses received the highest ratings across all 3 dimensions of effectiveness (favorability, discussion-shifting potential, and likelihood of changing bullying behavior), followed by AllyGPT, with policy reminders rated lowest. Qualitative feedback further emphasized that baseline GPT responses were perceived as natural and inclusive, while AllyGPT responses, although grounded in psychological theory, were sometimes viewed as overly direct. Policy reminders were considered clear but lacked persuasive impact. CONCLUSIONS: Our work showed that designing effective AI-generated bystander interventions requires a deep sensitivity to platform culture, social context, and user expectations. By combining psychological theory with adaptive, conversational design and ongoing feedback loops, future systems can better support bystanders, delivering interventions that are not only contextually appropriate but also socially resonant and behaviorally impactful. As such, this work serves as a foundation for scalable, human-centered AI systems that promote safer online spaces and users' mental well-being.
16 Apr 2026
Read appraisal →Journal of medical Internet research
A Health-Related Digital Ecological Momentary Assessment in Children (Aged 5-11 Years): Systematic Review
BACKGROUND: Digital ecological momentary assessment (EMA) collects data on experiences as they occur in daily life, capturing dynamic, context-sensitive experiences often missed by retrospective reporting. While EMA shows promise for pediatric health research, preadolescents have distinct socioemotional and cognitive characteristics likely to affect engagement. Existing reviews have not focused on the acceptability and feasibility of EMA protocols for this age group. OBJECTIVE: This review aimed to examine digital EMA protocols used with children aged 5-11 years across health domains, focusing on protocol characteristics, acceptability, and feasibility. We address 3 research questions (RQs)-RQ1: What are the characteristics of these protocols? RQ2: What is the feasibility and acceptability of these protocols? RQ3: What are the characteristics of high and low response rate protocols? METHODS: We searched 10 databases (CINAHL, Embase, ACM Digital Library, IEEE Xplore, Cochrane Library, PsycINFO, Web of Science, PubMed, Scopus, and MEDLINE) for peer-reviewed studies published up to October 2025. Eligible studies used EMA with children aged 5-11 years to collect health data via digital devices. Two researchers independently screened studies (SC and LT); one (SC) conducted quality assessment and data extraction. Findings were narratively synthesized. RESULTS: We identified 17 protocols across 37 studies. Most targeted nonclinical populations, used handheld devices, spanned 3-28 days, and applied interval-contingent prompting (RQ1). Response rates were available or calculable for 15 of 17 protocols, ranging from 48% to 92% (RQ2). Six protocols reported response rates of ≥80%. However, key data required for pooling (eg, raw counts for planned vs completed prompts) were missing or selectively reported. This contributed to 13 of 17 protocols being rated at critical risk of bias (ROBINS-I, v2). As a result, the strength of evidence was limited by poor reporting and high risk of bias. Facilitators included uncomplicated, engaging technology, reminders, and caregiver involvement. Barriers included device burden, restricted device access, difficulty with accurate reporting, stigma, limited device awareness, and insufficient caregiver support. High-response protocols (≥80%) often involved older children or clinical groups, ≥3-week duration, fixed schedules (≥20 items per prompt, 3 or 4 times per day), timing customization, and incentives (RQ3). CONCLUSIONS: This review provides the first systematic synthesis on preadolescents, offering insight into EMA protocol design beyond prior work treating children as a single group. By examining 17 EMA protocols, the review identifies gaps in developmental appropriateness and reporting quality, highlighting where the evidence may differ from adolescent and adult EMA research. The results suggest that digital EMA for preadolescents requires greater focus on child-centered design to increase acceptability and adherence, alongside improved reporting standards, so protocols can be meaningfully compared. With these advances, EMA could be more effectively integrated into pediatric health monitoring, tailored to the needs of different age groups.
16 Apr 2026
Read appraisal →Renal failure
Benefits of physical exercises in chronic kidney disease: a systematic review and meta-analysis of randomized controlled trials
Physical exercise has been proven to be beneficial for chronic kidney disease (CKD) patients; however, there is a lack of a comprehensive summary of existing literature, especially the results from randomized controlled trials (RCTs). We had conducted a systematic review and meta-analysis to evaluate the benefits of physical exercise in chronic kidney disease. Outcomes were classified into all-cause mortality, cardiovascular, pulmonary, and renal outcomes, inflammatory indices, laboratory tests, and physical indices. The risk of bias was assessed using the Cochrane criteria. Relative risk ratios with 95% confidence intervals (CIs) for categorical variables, and weighted mean difference or standardized mean differences with 95% CIs for continuous variables were pooled using a random-effects model. Publication bias was assessed using Funnel plot analysis and Egger's Test. At last, 82 studies were included, and the results of the meta-analysis show that the physical exercises can significantly reduce all-cause mortality, particularly in dialysis dependent patients. Cardiovascular function, reflected by 6-minute walk test and blood pressure and pulmonary function, reflected by peak oxygen uptake, forced expiratory volume in 1 second, and forced vital capacity, all improved after physical exercise interventions. Physical exercises helped to increase the dialysis adequacy and preserve the residual renal function. C-reactive protein and interleukin-6 levels decreased, and hemoglobin and albumin levels increased upon physical exercise interventions. The fat mass decreased after physical exercise interventions in non-dialysis patients. We concluded that physical exercise is beneficial for CKD patients, independent of the modes or locations of exercise.
16 Apr 2026
Read appraisal →BMJ open
Generative artificial intelligence-driven chatbots and medical misinformation: an accuracy, referencing and readability audit
OBJECTIVES: Artificial intelligence (AI)-driven chatbots have been rapidly adopted across research, education, business, marketing and medicine. Most interactions, however, come from non-experts using chatbots like search engines, including for everyday health and medical queries. DESIGN: We conducted an original study to audit chatbot responses in health and medical fields prone to misinformation. METHODS: Five popular chatbots were assessed: Gemini (Google), DeepSeek (High-Flyer), Meta AI (Meta), ChatGPT (OpenAI) and Grok (xAI). In February 2025, each chatbot was prompted with 10 questions from five categories: cancer, vaccines, stem cells, nutrition and athletic performance. We deployed an adversarial-like framework, using open- and closed-ended prompts designed to strain models toward misinformation or contraindicated advice. Two experts from each category rated responses as 'non-problematic', 'somewhat problematic' or 'highly problematic' using a coding matrix based on objective, predefined criteria. Citations were scored for accuracy and completeness, and each response was given a Flesch Reading Ease score. RESULTS: Nearly half (49.6%) of responses were problematic: 30% somewhat problematic and 19.6% highly problematic. Response quality did not differ significantly among chatbots (p=0.566) but Grok generated significantly more highly problematic responses than would be expected under a random distribution (z-score +2.07, p=0.038). Performance was strongest in vaccines (mean z-score -2.57) and cancer (-2.12), and weakest in stem cells (+1.25), athletic performance (+3.74) and nutrition (+4.35). Chatbot outputs were consistently expressed with confidence and certainty; from 250 total questions, there were only two refusals to answer (0.8%), both from Meta AI. Reference quality was poor, with a median completeness score of 40% (Q1-Q3: 20-67%). Chatbot hallucinations and fabricated citations precluded any chatbot from producing a fully accurate reference list. All readability scores were graded as 'Difficult' (30-50), equivalent to college sophomore-senior level. CONCLUSIONS: The audited chatbots performed poorly when answering questions in misinformation-prone health and medical fields. Continued deployment without public education and oversight risks amplifying misinformation.
16 Apr 2026
Read appraisal →Journal of affective disorders
Comorbid clinical and biomarker outcomes in patients with obsessive-compulsive disorder: An umbrella review and evidence map
BACKGROUND: Obsessive-compulsive disorder (OCD) is a chronic psychiatric condition with diverse comorbidities, yet outcome research remains limited. Thus, we aimed to systematically review existing meta-analyses of OCD-associated comorbid outcomes and assess the strength of evidence. METHODS: We conducted an umbrella review of meta-analyses, searching PubMed/MEDLINE, Embase, CINAHL, and Google Scholar up to July 7, 2025. Although we intended to include all studies related to OCD-associated comorbid outcomes, only observational studies were available. Effect sizes were recalculated using random-effects models, and all estimates were converted to equivalent standardized mean differences (eSMD) with 95 % confidence intervals (CIs). The methodological quality of the included reviews was assessed using the AMSTAR 2 tool, and the class of evidence (CE) for each association was graded according to predefined criteria (Class I-IV). RESULTS: We identified 17 meta-analyses that included 373 primary studies, covering 52 outcomes in 156,161 participants across 40 countries. Patients with OCD were associated with autistic traits outcomes, including restricted and repetitive behaviors (eSMD, 1.66 [95 % CI, 1.25-2.07]; CE = IV), and total autism-spectrum quotient score (1.40 [1.06-1.81]; CE = IV). OCD also showed associations of varying strength with several other outcomes, including suicidal attempt (0.64 [0.47-0.81]; CE = II) and toxoplasmosis infection (0.37 [0.15-0.59]; CE = III). Furthermore, quality of life was decreased across multiple domains in individuals with OCD (emotional, -1.47 [-1.96 to -0.98]; CE = II; global, -0.79 [-1.02 to -0.55]; CE = II; work/social, -1.21 [-1.72 to -0.69]; CE = III). CONCLUSION: Our study highlights the comprehensive impact of OCD, indicating associations with autism, suicidality, social-cognitive deficits, impaired quality of life, and neurobiological markers. STUDY REGISTRATION: PROSPERO CRD420251124380.
16 Apr 2026
Read appraisal →Journal of affective disorders
Development and validation of machine learning models to predict PTSD at multiple time points in hospitalized trauma patients
BACKGROUND: Posttraumatic stress disorder (PTSD) is a severe trauma-related mental disorder with high global burden. Early identification remains challenging, particularly in developing regions. Leveraging routinely collected clinical biomarkers may offer a scalable solution for timely risk detection. METHOD: This multicenter study utilized two independent prospective trauma cohorts to develop and externally validate machine learning models for predicting PTSD at 1, 3, and 6 months post-trauma. The development cohort consecutively enrolled 382 hospitalized trauma patients (Nov 2023-Dec 2024), while the external validation cohort included 204 patients (Oct 2021-Nov 2022). Predictors comprised psychosocial variables and routine clinical biochemical markers, including inflammatory indicators, liver and renal function markers, and hematological parameters. Five models were constructed (Logistic Regression, Random Forest, SVM, XGBoost, and Neural Network), with performance evaluated by AUC and feature importance interpreted via SHAP. RESULTS: Support Vector Machine achieved the best performance at 1 month (AUC = 0.84), while Random Forest models performed best at 3 and 6 months (AUC = 0.78 and 0.87). SHAP analysis indicated that ASDS were the most important predictors at all time points, with feature importance shifting over time. Acute stress and psychological state were dominant at 1 month, fearful experiences with physiological responses at 3 months, and chronic psychological burden and emotional state at 6 months. CONCLUSIONS: PTSD can be reliably predicted using psychosocial data and routine clinical biochemical markers. These findings support the integration of clinically accessible biological data into early PTSD risk screening, particularly in resource-limited settings.
15 Apr 2026
Read appraisal →Journal of affective disorders
Association of social isolation and loneliness with cancer prognosis: an analysis of the UK Biobank
BACKGROUND: Evidence is scarce for the association between social isolation and loneliness and prognosis of any cancer or other common cancer types. METHODS: To address this gap, we performed a cohort study from 2006 to 2022 using data from the UK Biobank (UKB). Social isolation and loneliness were identified based on the questionnaire of the UKB. Cases of death were obtained from the death registry, where both primary and contributory causes were recorded using ICD-10 codes. The Cox proportional hazard models were used to estimate hazard ratios (HRs) and associated 95% confidence intervals (CIs) of death in relation to social isolation and loneliness among patients with cancer. RESULTS: Among cancer patients studied, 6206 (9.6%) were socially isolated and 3130 (4.8%) reported loneliness. Over a median follow-up of 6.7 years, there were 2378 deaths (38.3%) among exposed patients and 16,566 deaths (29.1%) among unexposed patients. Social isolation was associated with poorer cancer prognosis overall (HR 1.21, 95% CI 1.16-1.26, P < 0.001), while loneliness correlated with a similar risk (HR 1.18, 95% CI 1.11-1.25, P < 0.001). Social isolation specifically impacted survival in colon, melanoma, breast, prostate, kidney, and bladder cancers, as well as myeloproliferative neoplasms. Loneliness was linked to poorer outcomes in breast, prostate, and bladder cancers. CONCLUSIONS: Our findings suggested that social support for these vulnerable patients might have the potential to improve prognosis.
15 Apr 2026
Read appraisal →Journal of affective disorders
Adverse psychosocial work exposures and 2-year incident prescription of psychotropic medications: a prospective French study using the national healthcare reimbursement database
OBJECTIVE: Despite the abundant literature on the associations between psychosocial work exposures and mental health outcomes, prospective studies using medico-administrative data are lacking. The objective was to study the associations between various psychosocial work exposures and incident prescription of psychotropic medications. METHODS: The study relied on three waves (2010, 2012, 2014) of the French ESPS survey (Health, Health Care and Insurance Survey) (baseline data), linked to the national database of healthcare reimbursements (follow-up data). Each survey wave was conducted among a randomly selected national sample of people aged 18+. The study included a total of 8689 observations among 7695 workers without psychotropic medication prescription within the 6 months preceding survey wave. Ten psychosocial work exposures (quantitative demands, tensions with the public, freedom, possibilities for learning new things, colleague support, recognition, salary satisfaction, job insecurity, temporary contract, and redundancy plan) were assessed at each survey wave. Covariates included gender, age, marital status, employee/self-employed worker, private/public sector, occupation, and full/part-time work. The outcome was psychotropic medication prescription within the 2 years following survey wave. Mixed effects Cox regression modelling was used. RESULTS: Seven of the ten psychosocial work exposures were associated with incident psychotropic medication prescription. Associations were observed more with incident prescription of antidepressants and anxiolytics than with hypnotics/sedatives. The number of psychosocial work exposures increased the risk linearly, except for hypnotics/sedatives. No gender interaction was found for any of these associations. CONCLUSION: The findings may support that poor psychosocial working conditions increase the risk of subsequent psychotropic medication prescription.
15 Apr 2026
Read appraisal →BMJ open
Regional disparities in insurance-covered cognitive behavioural therapy in Japan: a nationwide cross-sectional study using National Database Open Data, 2015-2023
OBJECTIVES: Cognitive behavioural therapy (CBT) is recommended as a first-line treatment for depression and anxiety disorders, but its utilisation under Japan's national health insurance remains poorly understood. This study aimed to describe CBT utilisation patterns, quantify regional disparities across prefectures and analyse temporal trends from fiscal year (FY)2015 to FY2023. DESIGN: This was a nationwide repeated cross-sectional study. SETTING: Japan's National Database of Health Insurance Claims and Specific Health Checkups Open Data (NDB Open Data), FY2015-2023. PARTICIPANTS: All patients who received insurance-covered CBT in FY2023, with a longitudinal comparison across FY2015-2023. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcomes were annual CBT claims and patient counts. The secondary outcomes included prefecture-level distribution, population-adjusted utilisation rates per 100 000 population, distribution by sex and age, monthly trends and temporal changes over 9 years. Regional variation in physician-delivered CBT was assessed using the coefficient of variation (CV) and extremal quotient (EQ). RESULTS: In FY2023, the total CBT claims numbered 38 045 with 8299 patients, representing only 0.14% of an estimated 6.03 million psychiatric patients. Physician-delivered CBT accounted for 99.6% (37 886 claims), whereas nurse-delivered CBT introduced in 2016 remained at 0.4% (159 claims). 13 of the 47 prefectures (27.7%) had zero or fewer than 10 claims. The population-adjusted physician-delivered CBT claims ranged from 370.96 per 100 000 in Okayama to 0.99 per 100 000 in Kumamoto, yielding an EQ of 375-fold. The CV among the 34 prefectures with measurable physician-delivered CBT was 174.8%. Despite indication expansions in 2016 and 2018, claims decreased by 9.9% from 42 216 in FY2015 to 38 045 in FY2023. CONCLUSIONS: Insurance-covered CBT in Japan remains severely underused, with significant regional disparities. Incremental policy measures, including indication expansions and nurse-delivered CBT, have failed to improve access. Fundamental system reforms, potentially including dedicated psychological therapy services, are needed to ensure equitable access to evidence-based psychological treatments.
15 Apr 2026
Read appraisal →BMJ sexual & reproductive health
Nurse and midwife interventions to improve access to contraception and abortion in primary care: a systematic review
OBJECTIVES: Amid the unmet need for contraception and safe abortion care globally, harnessing the capabilities of primary care nurses and midwives is vital for facilitating equitable access to these critical healthcare services. We aimed to evaluate the impact of interventions delivered by primary care nurses and/or midwives on facilitating access to contraception and abortion care. STUDY DESIGN: We conducted a systematic review in accordance with PRISMA guidelines and searched five electronic databases in September 2023. A narrative synthesis was conducted with analysis informed by the Levesque et al framework for access to healthcare. RESULTS: Twenty-three articles met the inclusion criteria; 20 related to contraception and three to abortion care. Access to contraception and abortion care was predominantly focused on addressing consumer-related factors such as perception of healthcare needs and support to engage with services. Findings suggested home visiting, telehealth and reproductive counselling interventions by primary care nurses and midwives can be effective at increasing women's access to contraception. There was some evidence these clinicians could be acceptable providers of medical abortion; however, there were no articles on procedural abortion. CONCLUSIONS: Primary care nurses and midwives have the potential to improve women's access to contraception care, particularly through the use of home visiting or telehealth strategies. However, evidence on how nurses and midwives can support access to abortion care is scarce and more research is needed, particularly for procedural abortion. Further research should also target under-studied access factors, including the acceptability of nurses and midwives providing contraception and abortion care and consumers' ability to reach and pay for this healthcare.
15 Apr 2026
Read appraisal →Journal of medical Internet research
Digital Monitoring of Pre-Exposure Prophylaxis Users Through Electronic Patient-Reported Outcome Measures and Electronic Patient-Reported Experience Measures: Multicenter Prospective Study on Feasibility, Safety, and Predictive Modeling of Digital Engagement
BACKGROUND: Digital health tools integrating electronic patient-reported outcome and experience measures (ePROMs/ePREMs) enable longitudinal monitoring of health-related quality of life (HRQoL), psychological well-being, and treatment satisfaction in pre-exposure prophylaxis (PrEP) users. However, determinants of sustained engagement with digital follow-up platforms remain insufficiently characterized. OBJECTIVE: To describe the feasibility of the Naveta-Phemium digital platform for longitudinal monitoring of safety, HRQoL, and treatment satisfaction among PrEP users, and to develop and internally validate a machine learning framework to characterize and predict engagement with digital follow-up. METHODS: A prospective observational study was conducted using the Naveta digital follow-up platform. HIV-negative adults at high risk of HIV infection received tenofovir disoproxil fumarate (245 mg) plus emtricitabine (200 mg). Clinical safety, HRQoL, and satisfaction were assessed using laboratory parameters and validated ePROMs/ePREMs (Hospital Anxiety and Depression Scale, Patient-Reported Outcome Measurement Information System Profile-29, Treatment Satisfaction Questionnaire for Medication, and Person-Centered Coordinated Care Experience Questionnaire). Engagement was defined at the questionnaire level and analyzed using the ALGOPROMIA-Classification framework with repeated stratified cross-validation. Model explainability was assessed using permutation-based Shapley Additive Explanations. RESULTS: A total of 81 participants contributed repeated questionnaire-level observations (mean PrEP duration 689 d). PrEP was well tolerated, with no moderate or severe adverse events; mild transient symptoms were mainly gastrointestinal (31/45, 68.9%) and neurological (26/45, 57.8%). Renal function remained stable (creatinine: 0.86 [SD 0.13] mg/dL; estimated glomerular filtration rate: P=.498). Psychological well-being and HRQoL remained stable (Hospital Anxiety and Depression Scale<7; Patient-Reported Outcome Measurement Information System Profile-29 near population norms). Treatment satisfaction was consistently high (Treatment Satisfaction Questionnaire for Medication≈85-87), and satisfaction with the NAVETA telemedicine model remained stable (8/10). Engagement showed clear sociodemographic and behavioral gradients. Ensemble-based machine learning models achieved good discrimination in predicting engagement (area under the curve≈0.82) across ≈12,300 questionnaire-level observations. Random forest was retained for robustness and consistency. Shapley Additive Explanations analysis highlighted lifestyle-related variables as the most influential predictors, with heterogeneous individual-level effects. CONCLUSIONS: Naveta enabled feasible telemedicine-based PrEP follow-up with preserved HRQoL, high satisfaction, and stable safety. Combining longitudinal ePROMs/ePREMs with explainable machine learning allowed detailed characterization of digital engagement, supporting digitally supported PrEP care optimization and informing future comparative and cost-effectiveness studies.
15 Apr 2026
Read appraisal →JMIR formative research
Comparing Large Language Models and Traditional Machine Translation Tools for Translating Medical Consultation Summaries: Quantitative Pilot Feasibility Study
BACKGROUND: Translation of medical consultation summaries is essential for equitable health care communication in culturally and linguistically diverse populations. While machine translation (MT) tools and large language models (LLMs) are widely accessible, their feasibility and safety for health care contexts remain underexplored. OBJECTIVE: This pilot study investigates the feasibility and limitations of using LLMs and traditional MT tools to translate medical consultation summaries from English into the most common languages other than English spoken in Australia-Arabic, Chinese (simplified written form), and Vietnamese. METHODS: Two simulated summaries-a simple patient-facing summary and a complex clinician-oriented interprofessional letter-were translated using 3 LLMs (GPT-4o, Llama-3.1, and Gemma-2) and 3 MT tools (Google Translate, Microsoft Bing Translator, and DeepL). Translations were benchmarked against professional third-party interpreter translations using Bilingual Evaluation Understudy, Character-level F-score, and Metric for Evaluation of Translation with Explicit Ordering metrics. RESULTS: The translation performance varied across languages, tools, and summary complexity when assessed using automatic evaluation metrics. Traditional MT tools outperformed LLMs on surface-level metrics, while LLMs showed relative strengths in semantic similarity for Vietnamese and Chinese. Arabic translations improved with complex input, suggesting morphological advantages. The metric-based evaluation highlighted feasibility but also risks, particularly in Chinese clinical contexts. CONCLUSIONS: This pilot study provides formative evidence of opportunities and limitations in applying artificial intelligence translation for health care communication. Findings underscore the importance of human oversight; domain-specific evaluation metrics; and further formative and clinical research to guide the safe, equitable use of artificial intelligence translation tools.
14 Apr 2026
Read appraisal →Journal of medical Internet research
Using Group Chats to Drive Behavior Change in Digital Health Interventions: Scoping Review and Realist Synthesis
BACKGROUND: Group chats on platforms such as WhatsApp (Meta Platforms, Inc), WeChat (Tencent Holdings Limited), and Telegram (Telegram FZ-LLC) are central to everyday communication in many settings, including across low- and middle-income countries and among groups often overlooked by one-to-one or app-based digital health tools. Yet their roles and underlying mechanisms as intentionally designed health interventions have not been comprehensively examined. OBJECTIVE: This scoping review with realist synthesis aimed to map the characteristics and reported outcomes of group chat-based health interventions and contextual conditions shaping their outcomes. It mapped intervention characteristics and identified context-mechanism-outcome (CMO) configurations driving behavior change. METHODS: We included empirical studies in which group chats were the primary digital component of the health intervention. Searches of PubMed, Embase, MEDLINE, Web of Science, and Scopus (2005-2026) and reference screening identified eligible studies. Data were extracted on study characteristics, health domains, settings, participants, platform, intervention features, and outcome domains. For the realist synthesis, CMO configurations were analyzed using reflexive thematic analysis informed by social cognitive theory and synthesized into a final program theory. RESULTS: Eighty-one studies were included. Publications increased sharply after 2020, with evidence clustering in mental health (25/81, 30.9%) and maternal and child health (20/81, 24.7%). Most studies enrolled adult participants, including pregnant or postpartum women, caregivers, and people managing chronic conditions. WhatsApp (38/81, 46.9%) and WeChat (21/81, 25.9%) were the most frequently studied platforms. Interventions were commonly delivered in clinical or community settings and typically involved mixed membership groups that included health professionals alongside participants (68/81, 84.0%). The realist synthesis identified 12 recurring CMO configurations across 5 domains: capability and actionability, confidence and motivation, modeling and norms, safe and supportive environment and access, and self-regulation and maintenance. These mechanisms were activated or suppressed by facilitation quality, group composition, cultural alignment, technological access, and social norms. The final program theory depicts group chats as dynamic systems where access, facilitation, and group structure shape how the domains amplify or dampen one another, explaining shifts from low engagement to high trust spaces sustaining behavior change. CONCLUSIONS: This review integrates descriptive mapping of interventions with realist program theory to explain how context and facilitation activate mechanisms of change, unlike prior reviews that have focused narrowly on effectiveness of digital modalities. This dual approach provides a practical, mechanism-focused basis for designing and scaling group chat interventions in practice, particularly given their potential as a low-cost, high-reach strategy embeddable within broader digital health programs. Realizing this potential depends on treating group chats as purposefully designed social environments, with deliberate attention to facilitation quality, equity-oriented access, and alignment between group structure, norms, and communication practices.
14 Apr 2026
Read appraisal →Disaster medicine and public health preparedness
The Beirut Pager Explosions of 2024: A Systematic Review of an Unprecedented Mass Casualty Event
OBJECTIVE: In September 2024, Lebanon experienced an unprecedented mass casualty incident involving the simultaneous detonation of thousands of weaponized pager devices. This systematic review characterizes the resulting injury patterns, surgical burden, and disaster-response lessons to help inform future preparedness and response strategies. METHODS: PubMed, Embase, Scopus, and Web of Science were searched for studies on casualties from the pager explosions. A random-effects meta-analysis estimated pooled prevalence of injuries by body region. RESULTS: Sixteen articles met inclusion criteria overall, comprising seven studies in the clinical synthesis and nine articles in the qualitative disaster-response synthesis. A consistent injury pattern predominantly affected the hands, face, and eyes. Specialty-specific cohorts demonstrated severe ocular destruction, frequent hand amputation, and a substantial operative burden. In the two comparable hospital-based cohorts eligible for meta-analysis, upper extremity injuries were most common (pooled prevalence 84%; 95% CI: 73-91%; I2 = 0%). The incident exposed critical weaknesses in triage, communication, and specialty surge capacity. CONCLUSION: The 2024 pager explosions produced a novel injury signature distinct from conventional blast trauma. These findings, while based on limited case series, underscore the urgent need for health care systems to develop flexible, adaptive disaster plans that can respond to the unique threats of unconventional warfare.
14 Apr 2026
Read appraisal →JMIR aging
Personalized Digital Care Program Allocation for Older Adults: Reinforcement Learning-Based Simulation Study
BACKGROUND: As the demand for innovative older adult care grows alongside a shortage of care workers, personalization is key to optimizing services and enhancing long-term sustainability. This study proposes an adaptive reinforcement learning (RL)-based framework to promote precision digital care by dynamically assigning care programs based on individuals' unique characteristics and evolving needs. Its effectiveness was evaluated through simulation-based experiments comparing multiple allocation methods within an artificial intelligence (AI)-powered care call service for older adults. OBJECTIVE: This study aimed to develop and evaluate an RL-based model for personalizing digital care program allocation to optimize care engagement and health outcomes among low-income older adults living alone. METHODS: We developed the framework by using contextual bandits, specifically Thompson Sampling, to maximize user outcomes. Four program allocation strategies were tested using a synthetic dataset of user features and program attributes. Simulations were conducted over multiple iterations to evaluate how the model adapts over time and optimizes program assignments compared with static methods. RESULTS: Four program allocation methods were compared across 100 simulation runs (n=3000 assignments per run) using 2 datasets (AI Call: n=1196; Community Health Survey [CHS]: n=72,812): (1) systematic allocation (baseline), (2) single best program based on population average, (3) idealized personalized delivery (theoretical upper bound), and (4) precision digital care using Thompson Sampling. Precision digital care outperformed baseline and population-average approaches, achieving outcomes comparable to the theoretical upper bound. Compared to systematic allocation, call success rates increased by 84.2% (AI Call) and 54.4% (CHS), Patient Health Questionnaire-2 depression scores decreased by 32.1% (AI Call) and 41.4% (CHS), and self-reported health scores improved by 19% (AI Call) and 22% (CHS). It also showed improved learning efficiency, refining assignments dynamically as it learned from user responses. CONCLUSIONS: Our findings emphasize the importance of personalization in digital care. We plan to refine and validate the model through a publicly funded AI care program for community-dwelling, low-income older adults living alone in the Republic of Korea. RL offers a scalable and effective approach to advance precision digital care delivery and support future innovations in aging services.
14 Apr 2026
Read appraisal →JMIR cancer
Leveraging Innovative Electronic Health Record Data to Characterize Social Determinants of Health Among Survivors of Cancer in Persistent Poverty Areas: Cross-Sectional Study
BACKGROUND: Residents in persistent poverty areas experience higher cancer mortality due to social determinants of health that negatively affect multiple factors, including health behaviors. OBJECTIVE: This study aimed to characterize demographic, clinical, and social determinant of health factors among survivors of cancer in persistent poverty areas using electronic health record (EHR) data-including an embedded social risk screener and natural language processing (NLP) of social work notes-to inform community-engaged adaptation of lifestyle interventions. METHODS: EHR data from a large multispecialty group practice were extracted for patients with cancer residing in zip codes inclusive of persistent poverty areas targeted for a health behavior intervention and receiving care between January 2018 and November 2023. Self-reported social determinant of health data were obtained using the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE) and through NLP of social histories from a social work visit. RESULTS: We identified 2672 unique patients with cancer, of whom 578 (21.6%) had PRAPARE data and 1597 (59.8%) had social history data available for analysis. The most common cancers among survivors (n=1420, 53.1% female; n=1299, 48.6% Black individuals; mean age 65.2, SD 13.7 years) included breast (n=536, 20.1%), prostate (n=400, 15%), and lymphoid or hematopoietic (n=323, 12.1%) cancer. Among survivors in persistent poverty areas (n=509, 19%; all with a high Social Vulnerability Index), 34.6% (176/509) were single, 55.4% (282/509) had Medicare coverage (with only 73/509, 14.3% having private insurance), 36.5% (186/509) had obesity, 63.9% (325/509) had hypertension, and 31.2% (159/509) had diabetes. Of survivors in persistent poverty areas with PRAPARE data, 15.8% (19/120) lacked transportation, 4.2% (5/120) lived with housing insecurity, and 6.7% (8/120) felt unsafe where they lived. CONCLUSIONS: Innovative EHR and NLP approaches identified several socioeconomic and safety-related challenges along with opportunities for health behavior interventions to leverage Medicare coverage and target multiple comorbidities when adapting interventions for survivors of cancer living in persistent poverty areas.
14 Apr 2026
Read appraisal →Psychological medicine
Cost-utility and cost-effectiveness of SELFIE, a transdiagnostic ecological momentary intervention for improving self-esteem in youth aged 12-26 years exposed to childhood adversity: Findings from a multicenter randomized controlled trial
BACKGROUND: A novel transdiagnostic blended Ecological Momentary Intervention (EMI) for improving self-esteem in youth who experienced childhood adversity has shown beneficial effects. However, evidence on the cost-effectiveness of SELFIE and EMIs overall is lacking. METHODS: In this RCT-based economic evaluation, participants aged 12-26 years with low self-esteem (<26 on the Rosenberg Self-Esteem Scale [RSES]) and experienced childhood adversity were recruited from specialized mental health services and the general population and randomly allocated to CAU (control condition) or CAU + SELFIE (experimental condition). The Trimbos/iMTA Questionnaire for Costs Associated with Psychiatric Illness (TiC-P), the RSES, and EQ-5D-5L were assessed at baseline, post-intervention, and 6-, 18-, and 24-month follow-up. Incremental cost-effectiveness (ICER) and cost-utility (ICUR) ratios, and acceptability curves, were generated. Sensitivity and subgroup analyses assessed robustness. RESULTS: From a societal perspective, the ICER presented €1,219 per improved point of self-esteem, and the ICUR presented €53,986 per QALY gained. The probability of cost-effectiveness was 26% at a willingness-to-pay (WTP) threshold of €20,000/QALY and 49% at €50,000/QALY. At €50,000/QALY, the probability of cost-effectiveness was 77% from a healthcare perspective (ICUR €15,671/QALY gained) and 87% for participants recruited from specialized mental health services (ICUR €-14,567/QALY gained). CONCLUSIONS: At the societal level, the SELFIE intervention exceeded the WTP threshold. Tests for robustness showed higher probabilities of cost-effectiveness from a healthcare perspective, likely reflecting the absence of educational productivity loss costs in the societal perspective, and in youth recruited from specialized mental health services. The innovative field of blended EMIs yields encouraging first results, urging more cost-effectiveness research.
14 Apr 2026
Read appraisal →Epidemiology and psychiatric sciences
Cross-cultural validity of the generalized anxiety disorder 7-item scale (GAD-7): a systematic review and standardized assessment
AIMS: The Generalized Anxiety Disorder 7-Item Scale (GAD-7) is a brief self-reported measure for screening for anxiety symptoms. However, the evidence about its cross-cultural validity is fragmentary and usually focused on specific settings. Therefore, we aimed to critically review and synthesize the existing evidence about the cross-cultural validity of the GAD-7. METHODS: We conducted a systematic review of studies assessing the cross-cultural validity of the GAD-7 in following the PRISMA guidelines. Additionally, the quality of the studies was assessed following the COSMIN guidelines, and the quality of the evidence was assessed with the GRADE. Data were synthesized narratively. RESULTS: Out of 1,965 unique records, 9 unique studies were deemed eligible for the COSMIN appraisal and the narrative synthesis (total sample: 11,894, 53.7% females and 20 different cultural groups). Most studies (7) had adequate quality and showed evidenced of the unitary structure of the GAD-7 across cultural groups. In 4 studies also assessing possible cultural bias, the effect on the general score was deemed negligible. CONCLUSIONS: The evidence about the cross-cultural validity of the GAD-7 is very limited. Although more research is needed, the evidence available shows that the GAD-7 could be a cross-culturally valid tool for the assessment of anxiety symptoms in clinical contexts and epidemiological studies. Until new high-quality evidence will be available, these results would constitute a key first step for supporting the use of the GAD-7 in multi-cultural clinical settings and to inform clinical, public health and global health decision making in relation to anxiety.
14 Apr 2026
Read appraisal →Journal of chromatography. A
Machine learning-assisted HS-GC-IMS for discrimination and traceability of baby bottles based on volatile fingerprints
Ensuring the safety of food contact materials, particularly baby bottles, is crucial for infant health. In this study, a comprehensive analytical strategy integrating headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) with machine learning-based chemometrics was developed to profile volatile organic compounds (VOCs) and achieve discrimination and traceability of materials and brands among nine baby bottles. A total of 87 VOCs were identified, with aldehydes, esters, alcohols, ketones being the most diverse groups, and aldehydes exhibiting the highest concentrations. Visual representations were established, clearly illustrating the fingerprint profiles of the various baby bottle samples. Unsupervised models, principal component analysis (PCA) and hierarchical cluster analysis (HCA), revealed distinct clustering patterns. In contrast, supervised models, including Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM), and deep learning models such as Convolutional Neural Network (CNN) and Transformers, were constructed to predict brand classification. Among them, RF was selected as the optimal model due to its superior performance-utility balance. Key discriminant markers were further determined by integrating the Variable Importance in Projection (VIP) scores from OPLS-DA with the feature importance from the RF model, significantly improving classification efficiency. This research proposes an effective and reliable analytical framework for rapid identification and traceability of baby bottles, offering valuable insights for anti-counterfeiting and safety assurance of food-contact materials.
12 Apr 2026
Read appraisal →Australian journal of primary health
National and international guidelines for preconception care and comparison with Australian guidelines: a systematic review
BACKGROUND: Guidelines for preconception care are resources that are systematically arranged based on evidence and local contexts to enhance the delivery of high-quality and consistent healthcare. The Royal Australian College of General Practitioners Guidelines (RACGP) for preventive activities in general practice (the Red Book) contains specific components of preconception care items, yet this guideline primarily focuses on general preventive healthcare and may not include a comprehensive list of preconception items based on more recent evidence. This review aimed to compare the recent RACGP guidelines (the 2024 Red Book) with national and international guidelines for preconception care. METHODS: Electronic databases, including PubMed, Embase, Web of Science, CINAHL, and Scopus, were systematically searched following Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. We also searched clinical guideline registries on professional organisations' websites. Searches were conducted from May to June 2024 and in July 2025. RESULTS: We identified seven other national and international guidelines that recommended what should be done as part of preconception health in clinical practice. Preconception care elements that were not included in the current RACGP guidelines that have evidence of effectiveness were the inclusion of men in preconception care, screening for intimate partners and domestic violence, screening for chlamydia and gonorrhoea infections, and screening for female genital mutilation as part of preconception care. CONCLUSIONS: This review identified four preconception care elements that may potentially improve the implementation of preconception care in Australian practice. This work informs the next steps towards developing a comprehensive preconception medical record tool for use in general practice.
12 Apr 2026
Read appraisal →Vaccine
Adenovirus type 5 vector-based COVID-19 vaccine does not increase the likelihood of HIV infection
BACKGROUND: There is a concern about the potential increased risk of acquiring HIV infection after vaccination with adenovirus type 5 (Ad5) vector-based vaccines. We aimed to investigate whether Ad5-nCoV increases the risk of HIV infection. METHODS: Between September 2020 and March 2021, a Phase 3 clinical trial was executed to evaluate the efficacy of Ad5-nCoV. This trial, employing a double-blind, randomized, and placebo-controlled design, enrolled 44,247 participants from 66 clinical sites spanning Argentina, Chile, Mexico, Russia, and Pakistan. Participants were allocated randomly in a 1:1 ratio to receive either Ad5-nCoV or a placebo, and their HIV-negative status was assessed by self-report and confirmed by HIV testing on a baseline blood sample at the end of the study. Consequently, individuals initially administered a placebo received one dose of Ad5-nCoV, while those initially given Ad5-nCoV finally received two doses, with an interval of approximately 6-10 months between administrations. The trial design and primary outcomes have been previously reported. This analysis involves a comprehensive assessment of the associations between pre-existing Ad5 neutralizing antibodies, HIV prevalence and incidence before and after vaccination while accounting for demographic variables. RESULTS: A total of 43,780 participants who had valid HIV baseline testing results were included in this study. Prior to vaccination, there was no discernible difference in HIV prevalence between the placebo group (0·39% of 21,877 participants) and the Ad5-nCoV group (0·38% of 21,893 participants). This similarity persisted when the data were stratified by country, gender, age, and race. Paired analyses assessing HIV incidence were conducted on participants who tested negative for HIV before vaccination, with data collected over a 6-month period post-vaccination. The results revealed notable similarity in HIV incidence across all groups: 0·29% for Group A (Ad5-nCoV group), 0·21% for Group B (Placebo group), 0·27% for group A + D (Ad5-nCoV group and 1 × Placebo+1 × Ad5-nCoV group), 0·1% for Group C (2 × Ad5-nCoV group), and 0·25% for Group A + C + D (participants who received at least one dose of Ad5-nCoV). Testing approximately 100 randomly chosen participants in each country revealed a similar distribution of pre-existing Ad5 neutralizing antibodies (Nab), with the ratio above a titer of 200 ranged from 65·42% to 67·71%. Notably, the heightened presence of pre-existing Ad5 Nab did not result in an increased risk of HIV infection. CONCLUSION: The Ad5-nCoV did not increase the short-term risk of HIV infection in this large and diverse sample of the general population, regardless of the presence of pre-existing Ad5 Nab providing valuable insights into the safety of Ad5 vector-based vaccines. CLINICALTRIALS: gov, NCT04526990.
12 Apr 2026
Read appraisal →BMJ open respiratory research
Occupational exposure to toxic particles and risk of pulmonary sarcoidosis: a systematic review and meta-analysis
INTRODUCTION: The onset of sarcoidosis is likely the result of a complex genetic-environment-immunological interaction. This systematic review and meta-analysis aimed to identify occupational toxic particles associated with an increased risk of developing pulmonary sarcoidosis. METHODS: Publications in English, published from January 2000 to January 2025, were searched in PubMed, Scopus and JSTOR. The risk of bias was assessed for all included studies. Sensitivity analyses stratified by study quality were conducted to evaluate the robustness of the findings and potential bias. To assess publication bias, a funnel plot was used when more than six studies were included in the analysis. RESULTS: Five categories of toxic particles were identified to be associated with increased risk of the onset of sarcoidosis: chemicals, inorganic dusts, metals, mixed dusts and fumes and organic dusts. The quantitative analysis includes data from 13 studies. The results suggested that occupational silica, pesticides, mould/mildew and World Trade Center ((WTC) dust exposures were associated with increased odds of pulmonary sarcoidosis. Sensitivity analysis confirmed the robustness of the association for WTC dust and mould, whereas the risk associated with silica appeared attenuated in high-quality studies. However, gold exposure was identified as a protective factor. CONCLUSION: Pulmonary sarcoidosis is associated with occupational silica, pesticides, WTC dust and mould. Future research should prioritise gene-environment interactions and granuloma mineralogy to refine preventive strategies and disease management.
12 Apr 2026
Read appraisal →BMJ paediatrics open
Which healthcare services did children and adolescents use before presentation at specialised outpatient clinics for post-COVID-19 condition? Descriptive findings from the Post-COVID Kids Bavaria study.
OBJECTIVE: Measuring the utilisation of healthcare services in children and adolescents with symptoms suggesting post-COVID-19 condition (PCC) until their presentation at specialised outpatient clinics (SOC). METHODS: 117 patients (aged 4-17 years) with symptoms suggesting PCC were recruited for study participation in SOCs of the comprehensive care network 'Post-COVID Kids Bavaria' for children and adolescents with PCC in Bavaria, Germany. Information on healthcare utilisation from their initial SARS-CoV-2 infection until presentation at an SOC was collected via telephone interviews with parents. RESULTS: Participants had a median of 6.5 physician contacts (Q1-Q3: 3.8-11.5), mainly in person (99.1%, n=116) and rarely used telemedicine (21.4%, n=25). Contacts were mainly with paediatricians (72.6%, n=85), followed by general practitioners (46.2%, n=50). Non-pharmacological measures were used by 56 participants (47.9 %), with therapies by Heilpraktiker and osteopaths being used most commonly (30.8%, n=36). 76 participants (65.0%) were prescribed medications, and 71 (60.7%) used non-prescribed medications or supplements. CONCLUSIONS: Children and adolescents with PCC symptoms frequently consult healthcare services, often self-initiated measures provided by Heilpraktiker and osteopaths, until their presentation at an SOC. This may be due to unclear care pathways. Paediatricians and general practitioners are key providers, making their expertise and strong connections with SOCs essential for early diagnosis and appropriate treatment.
12 Apr 2026
Read appraisal →Nature communications
Exposome-wide patterns predict brain health in aging
Promoting brain health is vital for well-being and reducing healthcare burdens. Brain health as measured with the Brain Age Gap (BAG) - the difference between chronological and predicted brain age- relates to many factors. However, a holistic view, integrating the range of factors an individual brain is exposed to, is missing for understanding how the exposome shapes brain health. After computing BAG as an indicator of grey matter (GM) health, we predicted it using machine learning based on 261 exposome variables (spanning biomedical, environmental, lifestyle, socio-affective, and early life domains) in UK Biobank participants. Exposome data can predict GM health with factors pertaining to cardiovascular and bone health, along with alcohol and smoking, nutrition and diabetes showing greater contribution to the prediction. In such domains, life period and duration of exposure appeared crucial. These findings call for early prevention in cardiovascular and metabolic health to promote life-long brain health.
12 Apr 2026
Read appraisal →Vaccine
Increasing HPV vaccine uptake using a "start at 9" strategy: A pilot program
BACKGROUND: Human papillomavirus (HPV) vaccine completion rates by 13 years remain suboptimal. Earlier HPV vaccination may result in improved timely completion rates. We aim to describe the impact of recommending HPV vaccine at 9 years of age on vaccine completion rates. METHODS: We implemented a multi-level program (including policy development, provider and office personnel education, electronic health record changes, and use of vaccine promotional items) to facilitate routine HPV vaccine recommendation at 9 years at 2 pediatric practices. Monthly chart reviews were performed 6 months before through 18 months after program implementation. Outcome measures included rates of HPV vaccination and documentation of HPV vaccine during the visit. Quarterly data (age, HPV vaccination status, gender, race, ethnicity, insurance, and primary care provider type) were obtained from the electronic health records of 9-12-year-olds served by the practice from baseline through 18 months after program implementation. RESULTS: Following program implementation, the median percentage of HPV vaccine uptake among 9-10-year-olds increased from 8% to 41% at the urban practice and from 3% to 23% at the suburban practice. Similarly, HPV vaccine completion rates among 9-12 year olds increased from 9% to 14%, p < 0.001 and from 6% to 16%, p < 0.001, respectively. Documentation of provider vaccine recommendation strongly correlated with HPV vaccination. CONCLUSION: Implementation of a multi-level program to routinely recommend the HPV vaccine at 9 years of age is feasible and effective in increasing in HPV vaccine completion by 13 years of age.
12 Apr 2026
Read appraisal →PloS one
Inconsistent condom use and its associated factors among female sex workers in African countries: Systematic review and meta-analysis
BACKGROUND: Inconsistent condom use represents the most proximal behavioral risk factor for acquisition and transmission of sexually transmitted infections, including human immunodeficiency virus. However, certain situations hinder female sex workers from practicing consistent condom use. This study aimed to assess the pooled estimate of inconsistent condom use among female sex workers and identify factors associated with it. METHODS: This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, 2020 reporting checklist. Electronic databases (PubMed, Cochrane Library, Epistemonikos, Hinari, and Science Direct), Google Scholar, and other university repositories were searched until March 20, 2024, based on the eligibility criteria. Three independent reviewers screened the titles, abstracts, and full texts. Two independent reviewers extracted the data. The Joanna Briggs Institute quality appraisal checklist was used. The Higgin's I² test was used to quantify heterogeneity. Pooled analysis was conducted using a random-effects model. Sensitivity and subgroup analyses were done. Publication bias was assessed using Egger's regression test and funnel plot. The pooled prevalence and statistical association were declared at a p-value < 0.05 with the 95% CI. RESULTS: A total of 24 studies involving 23,496 female sex workers with a median age of 27.3 years were included. The overall pooled prevalence of inconsistent condom use among FSW in Africa was estimated at 46.73% (95% CI: 37.60, 55.86), I² = 99.59%, and p = 0.00. Condom availability (AOR = 0.68; 95% CI: 0.50, 0.92), depression (AOR = 1.51; 95% CI: 1.00, 2.30), no education (AOR = 1.87; 95% CI: 1.19, 2.93), two or more nonpaying clients (AOR = 2.90; 95% CI: 1.51, 5.54), having >9 current client number (AOR = 0.46; 95% CI: 0.29, 0.74), violence (AOR = 1.74; 95% CI: 1.33, 2.27), and police harassment (AOR = 2.28; 95% CI: 1.03, 5.05) were significant factors. CONCLUSION AND RECOMMENDATION: Inconsistent condom use was high in Africa. Factors including availability of condoms, depression, and education, having two or more nonpaying clients, client numbers, violence, and police harassment were significant factors. Strategies like improving peer education, providing mental health support, empowering women, and improving female sex workers educational status, ensuring condom availability, and strengthening supply for easily accessible condoms can decrease inconsistent condom use and protect FSWs from STI including HIV.
11 Apr 2026
Read appraisal →JMIR aging
Global, Regional, and National Burden of Falls Among Older Adults Aged 65 Years and Above: Secondary Data Analysis of the Global Burden of Disease Study 2021
BACKGROUND: Falls are a leading cause of injury, disability, and death among older adults, posing significant public health challenges. However, comprehensive global analyses of fall-related burdens in older populations remain scarce. OBJECTIVE: This study aimed to explore the patterns and distribution of the global, regional, and national burden of falls among adults aged 65 years and older. METHODS: Data from the Global Burden of Disease study 2021 were used to assess the overall, disability, and mortality burden of falls among adults aged 65 years and older. Age-standardized rates of disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost were calculated to compare burdens across countries. Health inequalities were evaluated via the slope index of inequality and the concentration index. Frontier analysis identified optimal burden levels by sociodemographic index (SDI). Bayesian age-period-cohort models projected trends up to 2050. RESULTS: DALY age-standardized rates showed a U-shaped distribution across SDI regions: lower-SDI countries faced higher mortality burdens, while higher-SDI countries had elevated disability burdens. Despite an increase in absolute overall burden inequality from 1990 to 2021, absolute inequalities in YLDs and years of life lost declined, with DALYs and YLDs exhibiting relatively more balanced distributions. Frontier analysis pinpointed countries with the greatest burden reduction potential. Projections suggest decreasing overall and mortality burdens by 2050 but rising disability burdens. CONCLUSIONS: Higher- and lower-SDI countries face distinct fall-related challenges. Reducing cross-national health inequalities and closing gaps between the observed burden and the optimal burden level achievable at a similar SDI level are critical. Despite projected declines in the overall burden (DALYs), the rising disability burden (YLDs) could present evolving challenges, potentially underscoring the importance of proactive preparedness.
11 Apr 2026
Read appraisal →PloS one
Exploring barriers and enablers to diabetes self-care practice in Ethiopia, 2025: A qualitative systematic review
INTRODUCTION: Diabetes mellitus is a growing public health concern in Ethiopia, with increasing prevalence and a high proportion of undiagnosed cases. Effective self-care is crucial for managing diabetes; however, many patients face challenges ranging from personal beliefs to systemic and sociocultural constraints. Although multiple qualitative studies have explored these challenges, a synthesized, context-specific understanding that incorporates broader social and health system factors remains limited. This review aimed to synthesize qualitative evidence on barriers and facilitators of diabetes self-care practice in Ethiopia. METHODS: A qualitative systematic review was conducted in accordance with PRISMA 2020 and PRISMA-QS guidelines. A comprehensive search of PubMed/MEDLINE, Scopus, CINAHL, Web of Science, and Google Scholar was performed using relevant keywords and Medical Subject Headings. Eligible studies included primary qualitative and mixed-methods studies with extractable qualitative findings that explored diabetes self-care barriers and facilitators among patients, caregivers, or healthcare providers in Ethiopia. Purely quantitative studies, reviews, editorials, and studies conducted outside Ethiopia were excluded. Thematic synthesis was employed to integrate findings, and the GRADE-CERQual approach was used to assess confidence in the review findings. RESULTS: Eleven studies were included, comprising qualitative and mixed-methods designs conducted across diverse urban and semi-urban healthcare settings in Ethiopia. Study participants included adults with type 1 and type 2 diabetes, as well as healthcare professionals and caregivers. Six major barriers to diabetes self-care were identified: health system limitations, individual-level challenges, socioeconomic constraints, behavioral and lifestyle factors, cultural and social norms, and lack of social support. Key facilitators included strong family and social support, health education and counseling, patient motivation and skills, culturally aligned practices, and signs of health system readiness. CONCLUSION AND RECOMMENDATION: Diabetes self-care in Ethiopia is shaped by interconnected individual, cultural, and systemic factors. While substantial barriers persist, important enablers, particularly family involvement and supportive healthcare interactions, offer opportunities for improvement. Interventions should be culturally sensitive, community-centered, and supported by strengthened health systems. Policy efforts should prioritize integration of diabetes care into primary healthcare services, capacity building of healthcare providers, and incorporation of patients' lived experiences into care planning. Prospero registration number CRD420251033692.
11 Apr 2026
Read appraisal →Proceedings. Biological sciences
Statistical structure and the evolution of languages.
Human cultural development is marked by the emergence of new words and ideas, reflecting societal changes. But how does this evolution proceed? We use modern methods in natural language processing (namely, word embeddings) to measure statistical traces of cultural development, providing a testing ground to compare different models as to how this process works. We show that real embeddings of English and 21 other languages exhibit a series of previously unrecognized regularities. Specifically, these are: (i) frequency assortativity, where entities of high popularity cluster near other high-popularity entities; (ii) characteristic clustering velocity profiles due to aggregation into hierarchical structures; (iii) persistent temporal dynamics, where newly created entities appear disproportionately near other recent entries; and (iv) Taylor's law, implying that over time and across empirical semantic space the variance in new entity counts scales as a power of the mean, which helps systematize and quantify large historical fluctuations of neologisms. To explain these facts, we propose a class of generative models (specifically, directed preferential placement) that construct synthetic embeddings exhibiting similar regularities. We show that analogous regularities also occur in other datasets, suggesting that such generating models may shed light on new aspects of language and cultural evolution.
11 Apr 2026
Read appraisal →Journal of medical Internet research
Digital Discourse, Secondary Victimization, and Psychological Harm: Mixed-Methods Analysis of System Justification in the #MeToo Movement
BACKGROUND: The #MeToo movement, initiated in 2006 and amplified on social media in 2017, mobilized women worldwide to share experiences of sexual harassment and assault online. While the movement increased awareness, it also revealed deep social divisions in digital spaces. Supportive discussions promoted solidarity and healing, whereas antagonistic responses reinforced backlash and secondary victimization. In India, the Indian Entertainment Industry (IEI) became a focal point where survivors' disclosures highlighted structural gender inequalities. These polarized reactions function as digital-health signals, reflecting stigma, psychosocial distress, and conditions that shape women's safety and mental well-being. Examining these narratives as indicators of public health risk helps identify patterns of structural inequity and secondary mental health burdens among survivors. OBJECTIVE: This study examined online discourse surrounding #MeToo to identify forms of system-justifying narratives on social media and to assess how #MeTooIndia exposed institutional inequities within the IEI. METHODS: This mixed-methods study comprised 2 components. In study 1, natural language processing was applied to analyze global #MeToo Twitter (subsequently rebranded X) discourse. From an initial corpus of 350,000 tweets, 205,082 were preprocessed, and sentiment and stance detection analysis identified 18,416 tweets expressing negative attitudes toward the movement. Latent Dirichlet allocation topic modeling extracted 22 topics, 12 of which aligned with system-justification categories, revealing distinct lexical and semantic patterns related to gender, institutional, and power dynamics. Two trained coders manually annotated a subsample to ensure conceptual clarity and interrater reliability. Study 2 involved qualitative, semistructured interviews with 20 academic experts in film, gender, and media studies to gather opinions on how #MeTooIndia influenced institutional discourse in the IEI and how these dynamics translate into digital and mental health risks. RESULTS: Analysis of #MeToo Twitter discourse in study 1 identified 4 primary forms of system justification: by gender, by the institutional system, by backlash, and by victim-blaming. Gender and institutional system justifications were the most prevalent. Study 2 reinforced these findings, revealing how experts perceived #MeTooIndia as both empowering and constrained by entrenched institutional and cultural barriers. Together, our findings highlight the dual function of social media in promoting collective advocacy while reproducing conditions linked to gender-based violence, psychological stress, and reduced help-seeking-key digital and mental health concerns. CONCLUSIONS: This mixed-methods study reveals that digital discourse surrounding #MeToo often sustains existing gender and institutional hierarchies rather than dismantling them. Across Twitter data and expert interviews, gender and institutional system justifications emerged as dominant narratives, highlighting how online spaces can reinforce structural inequities while appearing progressive. Although #MeToo amplified visibility and awareness, its potential for lasting institutional change remains limited. These findings underscore the need for trauma-informed digital governance, public health recognition of online hostility as a psychosocial risk, and frameworks that situate digital activism to institutional reforms that support safety and mental well-being.
11 Apr 2026
Read appraisal →JMIR human factors
Evaluation of Wellby, a Cocreated Mobile App and Wearable to Support Stress Management and Overall Well-Being: Mixed Methods Acceptability and Usability Study
BACKGROUND: Digital well-being support tools can offer adolescents tailored interventions embedded in their digital environments. However, there is a lack of high-quality, evidence-based digital interventions specifically designed for young people's well-being needs. Wellby is a mobile app and wearable device cocreated with Irish secondary school students to support stress management and overall well-being. OBJECTIVE: This study aimed to evaluate the acceptability and usability of the Wellby system using the technology acceptance model, focusing on ease of use, perceived usefulness, and behavioral intention among Irish secondary school students. METHODS: A mixed methods acceptability and usability study was conducted with Irish secondary school students (n=43) across 3 schools: 2 mainstream secondary schools and 1 Youthreach center for early school leavers. Students accessed the Wellby mobile app for 8 weeks and received the custom wearable device for the final 4 weeks (April-May 2024). Wellby included mood tracking, to-do lists, educational resources, text-based health coaching, and heart rate variability biofeedback with guided breathing exercises. Acceptability and usability were evaluated using the user version of the Mobile App Rating Scale (uMARS), structured focus groups, and app engagement analytics. Secondary measures included baseline well-being questionnaires (Perceived Stress Scale, Pittsburgh Sleep Quality Index, and EPOCH Measure of Adolescent Well-Being). RESULTS: Among survey respondents (n=29), uMARS subscale scores were high: information quality (mean 4.2/5.0), functionality (4.1/5.0), and aesthetics (4.1/5.0). The perceived impact subscale showed the highest scores for well-being awareness (3.8/5.0) and help-seeking intention (3.9/5.0). Of survey respondents who participated in prior co-design sessions, 88% (21/24) and 83% (20/24) felt the wearable and app, respectively, aligned with their co-design feedback. App engagement more than doubled following the introduction of the wearable and revealed that the wearable tab was most accessed (643/1688, 38% of interactions), followed by the home (430/1688, 25%), resources (338/1688, 20%), and coaching (277/1688, 16%) tabs. Focus group feedback highlighted the mood tracker as the most valued feature and identified technical improvements, including better battery life, enhanced Bluetooth connectivity, and more personalization options. CONCLUSIONS: This study demonstrates that cocreated digital well-being tools can achieve high acceptability and usability with Irish secondary school students. Applying the technology acceptance model effectively captured student experience through mixed methods feedback. Students particularly valued self-tracking and personalization features over coaching or educational features. These findings highlight the importance of aligning digital technologies with adolescents' needs and preferences, such as features that encourage increased autonomy and identity formation. Future iterations of Wellby should address the technical limitations while continuing the involvement of students to adapt to their developmental needs and maintain high acceptability.
11 Apr 2026
Read appraisal →Journal of epidemiology and community health
Utilisation of in-person and telehealth care among US adults with loneliness and social isolation
BACKGROUND: Telehealth has become a critical tool for improving access to care among populations facing physical barriers to in-person care. However, its potential role in delivering care to adults with social barriers remains underexplored. We examined whether adults with loneliness or social isolation are more likely to use telehealth care versus in-person care compared to adults without loneliness or social isolation. METHODS: This cross-sectional study analysed data for US adults in the 2021 Medical Expenditure Panel Survey. Loneliness and social isolation were measured using the UCLA Loneliness Scale and the Berkman-Syme Social Network Index. Three indicators of healthcare utilisation were used as outcomes: in-person care only, telehealth care only and a combination of both. RESULTS: Among adults experiencing loneliness and social isolation, the likelihood of using only in-person care was lower by 4.1 (95% CI -6.1 to -2.1) and 2.8 (95% CI -5 to -0.6) percentage points. In contrast, the likelihood of using only telehealth care was higher by 2.6 (1.1-4.2) and 5.4 (3.9-6.9). The likelihood of using both in-person and telehealth care was also higher by 2.3 (0.7-3.9) and 5.2 (3.7-6.7), but telehealth was used more frequently than in-person care. Furthermore, telehealth utilisation for mental health services was higher among adults experiencing loneliness or social isolation. CONCLUSION: Compared with adults who are not lonely or socially isolated, adults experiencing loneliness and social isolation are more likely to use telehealth and less likely to use in-person care. Telehealth may serve as a viable alternative for individuals facing social challenges in accessing in-person services.
11 Apr 2026
Read appraisal →International journal for equity in health
Community participation in responding to health misinformation
Responses to health misinformation increasingly emphasize the importance of community engagement, yet the role of participation and power sharing remains under-theorized and inconsistently described in the peer-reviewed literature. Drawing on findings from the systematic review Overcoming Health Misinformation in Marginalized Groups, which examined 32 studies evaluating approaches to tackling health misinformation, we reflect on how the depth and quality of community participation shape trust, engagement, and intervention success. We argue that sustained partnership, shared decision-making, and local ownership enhance message credibility and reach by embedding health information within trusted social contexts. We propose strengthening equity-focused responses through structured reporting tools that center power, trust, and co-production as practical design principles rather than implementation add-ons. Making participation visible is critical if community engagement is to move beyond rhetoric and contribute meaningfully to addressing health misinformation in contexts of low institutional trust.
11 Apr 2026
Read appraisal →Acta dermato-venereologica
Predicting Melanoma Impact on the Swedish Healthcare System from the Adult Population Using Machine Learning on Registry Data
Melanoma incidence has increased in Western countries over the past 50 years, leading to significant healthcare costs. In Sweden, comprehensive healthcare registries enable large-scale prediction studies using machine learning. Several machine learning models were evaluated to predict melanoma diagnoses using Swedish registry data, assessing the added value of diagnostic and medication data beyond demographics. The study included all adults in Sweden with continuous residency for 9.5 years (n = 6,036,186). The outcome was a melanoma diagnosis, including melanoma in situ, recorded within 5 years after the index date (31 December 2014). Predictors included age, sex, income, education, marital status, region of birth, diagnoses, and dispensed drugs. Models tested were logistic regression, gradient boosting, random forests, and a neural network. A total of 38,582 individuals (0.64%) developed melanoma. The gradient boosting model using all predictors performed best, with an area under the receiving operating characteristics curve (AUC) of 0.735 (95% confidence interval [CI], 0.725-0.746). When diagnosis and medication data were excluded, AUC dropped to 0.681 (95% CI: 0.670-0.691). The findings highlight that including healthcare codes improves predictive performance, and demonstrate the utility of Swedish registries for computational phenotyping. This approach may support early detection of melanoma and targeted follow-up.
10 Apr 2026
Read appraisal →PloS one
Prevalence and determinants of inadequately controlled diabetes in Qatar's public primary care settings: A cross-sectional study
BACKGROUND: The prevalence of type 2 diabetes mellitus (T2DM) is rapidly increasing worldwide, causing serious morbidity and mortality. Proper management and control of T2DM are essential in slowing and reducing complications. Measuring the adequacy of diabetic control, therefore is one of the ways of evaluating the success of health care system and the individuals in addressing disease morbidity and mortality. This study was proposed to assess the extent of uncontrolled T2DM in ambulatory adults managed in the public primary care settings of Qatar over five years. In addition, it aimed to predict the risk of uncontrolled disease based on age, sex, nationality and comorbidity. METHODS: A cross sectional review of Electronic Health Records of 84,512 adult individuals with T2DM having at least one HbA1c blood test result per year during the 5 years study period (1st January 2018, to 31st December 2022) was analyzed. The term "inadequately controlled" T2DM was used to define an individual with HbA1c measurements of 7% or higher. RESULTS: The yearly prevalence of inadequately controlled T2DM remained stable at a high rate (53%) during the last three years of observations. Aging increases the probability of having inadequately controlled T2DM, but this was attributed to comorbidities. Adjusting for those comorbidities will show that younger ages are the ones at higher risk of being uncontrolled. Additionally, the study reported that hypertension and dyslipidemia are the most frequently prevalent comorbidities, nevertheless retinopathy, although less frequent, was the most important predictor for inadequately controlled T2DM. CONCLUSIONS: The study highlights the significant healthcare challenge posed by T2DM in Qatar due to its high prevalence and associated complications. Males, South Asian ethnic background and Qatari locals have the highest probability of being inadequately controlled. Overall, the study emphasizes the need for targeted interventions to address the challenges of controlling diabetes, particularly among high-risk groups identified in the study.
10 Apr 2026
Read appraisal →JMIR mHealth and uHealth
Trust and Use of Recommendations for Health Apps Among European Residents: Cross-Sectional Survey
BACKGROUND: There is growing recognition of the role of health apps in addressing health care system challenges, yet app quality and evidence vary widely, and consumers have little decision support at the point of download. OBJECTIVE: This study aimed to explore which sources of recommendations European residents use and trust when choosing health apps and whether residents support government review and rating of health apps. METHODS: We conducted a cross-sectional online survey (December 7, 2022, to February 16, 2023) in 26 languages targeting residents of the European Economic Area, the United Kingdom, and Ukraine. The survey contained 11 questions covering demographics, types of apps used, sources of advice used and trusted, and views on government review and rating. We included only fully completed responses (N=1228). Descriptive statistics are presented as counts and percentages. For subgroup analyses, we dichotomized trust responses ("I trust" vs other responses) and tested associations with gender (Fisher exact test), age group, and education level (chi-square test); an adjusted significance threshold was applied (P<.004) to account for multiple testing. We followed the CHERRIES (Checklist for Reporting Results of Internet E-Surveys) guidelines for reporting online surveys and STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) recommendations for observational studies. RESULTS: A total of 1228 respondents from 33 countries completed the survey; 1110 (90.4%) reported using one or more health apps. COVID-19 apps (763/1228, 62.1%) and activity apps (737/1228, 60.0%) were the most frequently used, whereas disease management (86/1228, 7.0%), diagnostic (77/1228, 6.3%), and treatment apps (70/1228, 5.7%) were the least used. Sources used to choose apps included family and friends (434/1228, 35.3%), health professionals (412/1228, 33.6%), and government or health authorities (358/1228, 29.2%). The most trusted sources were health professionals (987/1228, 80.4%), pharmacists (750/1228, 61.1%), and government or health authorities (736/1228, 59.9%). No statistically significant differences in trust by gender were observed (all P>.0038). Some differences by age and education were observed for select sources (eg, government or health authorities: χ21=8.546; P=.003; family and friends: χ2=19.133; P<.001). Overall, 1060 (86.3%) of 1228 respondents supported government review and rating of health apps (either directly or by commissioning another organization). CONCLUSIONS: In this large multilingual European survey, most respondents reported experience with health apps and placed greatest trust in health professionals, pharmacists, and government or health authorities, yet professional recommendations were used less often than informal sources. There is clear public support for government-led review and rating schemes to guide consumer choice. Efforts to make trustworthy, easy-to-find information available at the point of download and to support health care professionals in recommending high-quality apps could help bridge the gap between trusted and used sources.
10 Apr 2026
Read appraisal →Microbiology spectrum
PneumoWiki: a pan-genome-based database for the pathogen Streptococcus pneumoniae
UNLABELLED: The Gram-positive bacterium Streptococcus pneumoniae is a major human pathogen that exhibits more than 100 different capsular serotypes and considerable genomic variability. S. pneumoniae is also an important model organism for basic and biomedical research, with a number of strains with different characteristics being used. To address this, we have created the manually curated pan-genome database PneumoWiki (https://pneumowiki.med.uni-greifswald.de) that integrates genomic data of 43 S. pneumoniae strains with various aspects of functional annotation. All data relating to a specific gene and gene product are compiled on a Gene page. In addition to the gene and protein sequences and annotation from NCBI RefSeq, this includes, for example, data on gene expression, protein function, and localization. The information is supplemented with links to the data sources as well as to other databases and relevant literature. The basic concept of PneumoWiki is the interlinked presentation of pan-genome-based and strain-specific information. Therefore, register tabs with strain names at the top of the Gene pages allow switching between orthologous genes and the corresponding pan-genome page. The pan-genome gene pages contain a summary with functional information and the occurrence of the gene, an ortholog table for the 43 S. pneumoniae strains, a multiple-strain genome viewer as well as a protein sequence alignment. PneumoWiki was developed as a user-friendly tool and is available free of charge. The data collected in PneumoWiki are accessible via various download options. Overall, PneumoWiki is a resource for the research community that supports the analysis and interpretation of experimental data and, in particular, enables the integration of the knowledge available for different S. pneumoniae strains. IMPORTANCE: Databases that integrate and curate the large amounts of genomic data and functional information available for well-studied organisms play an increasingly important role in many areas of life sciences, including infection research. Streptococcus pneumoniae is a major human pathogen associated with high morbidity and mortality rates. The species exhibits high variability in its genome sequence, and a number of strains with different characteristics are used in pneumococcal research. We created the wiki-type database PneumoWiki to provide researchers with curated, up-to-date information on a range of pneumococcal genomes, focusing on the individual genes and encoded proteins and their functional annotation. The key feature of PneumoWiki is the pan-genome approach, which allows combining information of individual strains, thereby supporting the analysis of experimental data and comparisons between studies using different strains. In this way, the database becomes a valuable research tool that can contribute to a better understanding of pneumococcal physiology.
10 Apr 2026
Read appraisal →Journal of medical Internet research
Preferences for Personalized Text Message Appointment Reminders Among Outpatients in a Universal Health System: Cross-Sectional Study
BACKGROUND: SMS text messaging reminders are widely used to reduce missed outpatient appointments; however, evidence remains limited regarding which types of reminder content patients prefer, particularly within East Asian universal health systems. In Taiwan, minimal financial barriers to care and unrestricted access to secondary and tertiary hospitals contribute to high outpatient visit volumes and persistent no-show rates. These contextual features underscore the need for behaviorally informed and demographically tailored reminder strategies rather than uniform messaging approaches. OBJECTIVE: This study aimed to examine patient preferences for 6 theory-guided SMS appointment reminder types and to identify the predictors of reminder preference related to demographic characteristics and health care utilization, with the goal of informing personalized reminder design for a forthcoming randomized controlled trial. METHODS: We conducted a cross-sectional online survey among adults in Taiwan with prior outpatient experience. Six SMS reminder prototypes were developed based on behavioral communication principles and validated by a multidisciplinary expert panel using item-level content validity indices. Participants selected their preferred SMS reminder type and reported sociodemographic characteristics and recent health care utilization. Bivariate associations were examined using chi-square tests and one-way ANOVA, with Benjamini-Hochberg false discovery rate correction applied to control for multiple testing. To identify independent predictors of SMS reminder preference while adjusting for potential confounding, we fitted a multinomial logistic regression model with all covariates entered simultaneously. RESULTS: A total of 1095 respondents completed the survey. General reminders and messages referencing prior missed appointments were most frequently preferred, whereas empathy-based or relationally framed messages were selected less often. In false discovery rate-adjusted univariate analyses, both age and sex were associated with SMS reminder preference. However, in the fully adjusted multinomial logistic regression model, age emerged as the only statistically significant independent predictor. Participants younger than 50 years were significantly more likely to prefer alternative reminder message types compared with the general reminder (adjusted odds ratio 1.64, 95% CI 1.18-2.28; P=.003). Sex did not retain statistical significance after multivariable adjustment. Other sociodemographic characteristics and health care utilization variables, including education level, employment status, residential region, outpatient visit frequency, and recent missed appointments history, were not independently associated with reminder preference. CONCLUSIONS: Preferences for outpatient SMS reminder content vary systematically, with age representing the most robust independent predictor. Across the sample, concise and behavior-focused reminders were preferred over empathy-oriented or relational formats. These findings support age-informed tailoring of SMS reminder content and provide content-validated SMS prototypes for use in subsequent interventional research. The results offer formative evidence to guide the design of randomized trials aimed at reducing outpatient no-shows and improving the efficiency of ambulatory care delivery in Taiwan's universal health care system.
10 Apr 2026
Read appraisal →The Tohoku journal of experimental medicine
Age-Specific Trends and Health Status of Children Aged 12-19 Years with Specified Chronic Pediatric Diseases in Japan - Insights from a National Database Study
Japan has a national financial assistance program called the "Specified Chronic Pediatric Diseases of Japan" (SCPDJ; also called "Shouman" in Japanese) for children with chronic diseases designated by the Japanese Ministry of Health, Labour and Welfare. The information of registrants in the system is digitized for research. We utilized the database to clarify the characteristics of children with diseases designated by the SCPDJ program. Analysis was performed with a particular focus on patients aged 12-19 years, which are considered the important ages for transition support from pediatric to adult medical care. The data included 69,061 cases aged 0 to 19 years from April 2016 to March 2017. The number of registrants showed a cumulative increase from 2 years toward adulthood. There were four distribution patterns for registered age and age at onset by disease category: 1) both age and age of onset peaked at age 0; 2) age distribution was mostly flat, while the most common age of onset was age 0; 3) age distribution peaked in older age groups, while age of onset of 0 was most common; and 4) both age and age of onset peaked at older ages. Approximately half of the patients aged 12-19 years were diagnosed after reaching school age. Although the disease condition of most patients remained good, some aged 12-19 years experienced exacerbation. The database was analyzed to provide an overview of children with diseases designated by the SCPDJ program and issues related to transition to adult care systems.
10 Apr 2026
Read appraisal →The New England journal of medicine
Multifaceted Strategies for Hypertension Control in Low-Income Patients
BACKGROUND: Uncontrolled hypertension disproportionately affects populations that have substantial health disparities. Data regarding the effectiveness and implementation of multifaceted, team-based strategies for hypertension control among low-income patients are lacking. METHODS: We randomly assigned federally qualified health center clinics in Louisiana and Mississippi to use either a multifaceted implementation strategy (intervention group) or enhanced usual care (control group) for hypertension control. The intervention included team-based care, protocol-based intensive blood-pressure management, blood-pressure audit and feedback, health coaching on lifestyle changes and medication adherence, and home blood-pressure monitoring. Enhanced usual care involved educating physicians about clinical guidelines for hypertension. The primary effectiveness outcome was the mean change in systolic blood pressure from baseline to 18 months. The primary implementation outcome was the adherence summary score (on a scale of 0 to 4, with higher scores indicating better adherence to blood-pressure management). RESULTS: A total of 36 clinics underwent randomization. Among these clinics, we enrolled 1272 patients with uncontrolled hypertension who were 40 years of age or older; 642 were in the intervention group and 630 were in the control group. The mean age of the patients was 58.8 years, 56.7% were women, 63.4% were Black, 75.9% were unemployed, and 73.4% had a family income of less than $25,000 per year. At 18 months, the mean change from baseline in the systolic blood pressure was -15.5 mm Hg (95% confidence interval [CI], -17.4 to -13.6) in the intervention group and -9.1 mm Hg (95% CI, -11.0 to -7.2) in the control group (between-group difference, -6.4 mm Hg; 95% CI, -9.0 to -3.8; P<0.001). The mean adherence summary score over the 18-month follow-up period was 2.8 (95% CI, 2.7 to 2.9) in the intervention group and 2.1 (95% CI, 2.0 to 2.2) in the control group (between-group difference, 0.7 points; 95% CI, 0.6 to 0.8; P<0.001). Serious adverse events occurred in 20.9% of the patients in the intervention group and in 21.7% of those in the control group. CONCLUSIONS: Among low-income patients with hypertension, a multifaceted, team-based implementation strategy resulted in a significantly greater reduction in systolic blood pressure than enhanced usual care. (Funded by the National Heart, Lung, and Blood Institute and others; IMPACTS-BP ClinicalTrials.gov number, NCT03483662.).
9 Apr 2026
Read appraisal →Sexual health
Resilience of STI service delivery in community-based organizations during the 2024 armed conflict: insights from Lebanon.
This study explores the potential impact of war on STI services in Lebanon. Programmatic STI service data from Lebanon were analyzed, alongside a targeted review of the literature on conflict-affected settings, using public health databases covering the period 2014-2024. Evidence-based STI service packages for conflict settings remain limited. Drawing insights from the COVID-19 crisis, periods of emergencies are associated with an elevated risk of STI surges among key populations. Programmatic data from the conflict further demonstrated this increased risk, reflected in reductions in prevention and early detection activities compared with pre- and post-conflict periods. Self-care and outreach service packages could be critical in these contexts. Community-based organizations (CBOs) should adapt STI services to the wartime environment and evaluate the effectiveness of these interventions post-conflict. CBOs are encouraged to prioritize the implementation of self-care modalities for STI prevention and early detection, expand the availability of telehealth services, and deploy mobile clinics to maximize service continuity. This editorial analyzes STI service delivery within the specific context of the Lebanese war.
9 Apr 2026
Read appraisal →Sexual health
Co-creation and evaluation of people-centered mobile health messages to promote PrEP adherence among GBMSM in China: a feasibility study
BACKGROUND: Co-creation has the potential to generate people-centered mobile health (mHealth) interventions to improve PrEP adherence. This study generated people-centered mHealth messages with Chinese gay, bisexual and other men who have sex with men (GBMSM) via a structured co-creation approach, and evaluated the messages quality, and assessed the feasibility of the co-creation approach. METHODS: A three-step co-creation framework was implemented with 19 GBMSM PrEP users and six HIV researchers between 2021 and 2023. Messages were assessed via 10-point scales, and the degree of usefulness by co-creators and 783 participants from a PrEP demonstration trial. Thematic analysis identified PrEP adherence barriers and participants' reflections from meeting notes and materials, with descriptive statistics summarizing evaluation results. RESULTS: Four levels of PrEP adherence barriers were identified (insufficient education, efficacy concerns, inadequate behavioral skills, PrEP stigma). Based on these barriers, 25 mHealth messages (19 posters, three videos, three text messages) were co-created, covering nine themes (e.g. missed dose coping, side-effect management). Seventeen high-quality messages were selected, with mean scores of 8.25 (relevance), 7.86 (appropriateness) and 7.25 (elaboration). Among GBMSM PrEP users who received the messages, 90.4% (708/783) valued the co-created messages as helpful. Reflections from the co-creators highlighted the value of the participatory process, confirming that co-creation effectively engages GBMSM PrEP users. CONCLUSIONS: Co-creation groups are feasible for Chinese GBMSM to identify context-specific PrEP adherence barriers and develop people-centered mHealth messages, supporting the value of co-creation for PrEP adherence intervention development in this population.
9 Apr 2026
Read appraisal →JMIR mHealth and uHealth
Promoting Self-Regulated Social Media Use on Smartphones With a Mobile Intervention App (Wellspent): Randomized Controlled Trial
BACKGROUND: Problematic social media use has been linked to reduced well-being and impulse control difficulties. While digital self-control apps show potential for reducing general app usage, they often lack customization, leading to limited effectiveness and increased user resistance. Their impact on problematic social media use remains uncertain. OBJECTIVE: This study evaluates the effectiveness of the Wellspent app, a customizable mobile intervention app designed to promote self-regulated social media use by targeting user-defined problematic app use and offering tailored behavioral nudges. METHODS: In a 3-week randomized controlled trial, 70 iPhone users (mean age 26.2, SD 5.6 years; 47/70, 67% female), regularly using at least 1 social media app, were randomly assigned to an intervention (n=35) or control group (n=35). The intervention group received personalized full-screen reminders with the option to quit or continue social media app use whenever an app session exceeded a self-defined time limit. Participants completed weekly online surveys measuring problematic social media use, problematic smartphone use, self-efficacy, and daily screen time on their most problematic app. Linear mixed models tested intervention effects. RESULTS: While no significant reduction in problematic social media use or increase in self-efficacy was observed, the intervention group showed a significant reduction in daily screen time on their most problematic app by approximately 29 minutes (estimate=-29.35, SE 6.84, 95% CI -42.79 to -15.99; P<.001), and a significant decrease in perceived problematic smartphone use (estimate=-0.46, SE 0.18, 95% CI -0.80 to -0.11; P=.01). CONCLUSIONS: The Wellspent app demonstrated short-term efficacy in reducing problematic smartphone use. By allowing users to tailor interventions to their personal goals, the app shows promise as a self-directed tool to support healthier digital habits. Further research should explore long-term effects and feature-specific impacts.
9 Apr 2026
Read appraisal →The New England journal of medicine
Immunogenicity and Safety of vYF, a Yellow Fever Vaccine - A Phase 2 Trial
BACKGROUND: A next-generation, live-attenuated yellow fever vaccine, vYF, was developed in Vero cells to improve vaccine supply and availability. The safety of and immune response to vYF as compared with those of the licensed yellow fever vaccine, YF-VAX, are unclear. METHODS: In this year 1 interim analysis of a phase 2, observer-blinded, randomized, active-controlled trial, we randomly assigned healthy adults 18 to 60 years of age in a 2:1 ratio to receive vYF or YF-VAX as a single vaccine injection on day 1. Neutralizing antibody titers were measured on day 29, month 6, and year 1. The primary analysis focused on the per-protocol population, which included participants with no history of yellow fever infection or vaccination and with no protocol deviations. Noninferiority would be shown if the lower limit of the two-sided 95% confidence interval of the between-group difference in the percentage of participants with seroconversion was greater than -5 percentage points on day 29. RESULTS: A total of 568 participants were enrolled: 382 in the vYF group and 186 in the YF-VAX group; 329 and 156 participants, respectively, were included in the per-protocol population for the noninferiority analysis. Seroconversion by day 29 occurred in 99.7% of participants receiving vYF and 99.4% of those receiving YF-VAX (difference, 0.3 percentage points; 95% confidence interval, -1.2 to 3.2, which met the criterion for noninferiority). Neutralizing antibody geometric mean titers were similar in the two vaccine groups, peaking on day 29 (in the vYF group, 1:2654 among participants with no history of yellow fever infection or vaccination and 1:1312 among participants with a history of yellow fever infection or vaccination; in the YF-VAX group, 1:3147 and 1:1079, respectively), then decreasing through 1 year after vaccination (in the vYF group, 1:401 among participants with no history of yellow fever infection or vaccination and 1:490 among participants with a history of yellow fever infection or vaccination; in the YF-VAX group, 1:548 and 1:646, respectively). No major safety concerns were identified. The safety profiles were similar in the two vaccine groups: solicited adverse events were reported by 208 of 367 participants (56.7%) in the vYF group and 113 of 185 participants (61.1%) in the YF-VAX group, and unsolicited adverse events were reported by 99 of 379 participants (26.1%) and 39 of 186 participants (21.0%), respectively. CONCLUSIONS: In this trial, vYF had immunogenicity and safety profiles similar to those of YF-VAX. (Funded by Sanofi; ClinicalTrials.gov number, NCT04942210.).
9 Apr 2026
Read appraisal →Sexual health
E-screening for sexually transmissible infections and blood-borne viruses in New South Wales, Australia: a cost analysis.
BACKGROUND: MyCheck is an e-testing pathway, first implemented at Sydney Sexual Health Centre, which enhances access to STI/HIV testing via telehealth and off-site sample collection; thus, reducing clinic visits. This study evaluates MyCheck's direct and indirect costs versus standard in-person screening (Xpress). METHODS: A 12-month bottom-up cost analysis from a societal perspective compared MyCheck and Xpress. Direct medical (health system), direct non-medical (patient travel) and indirect non-medical (productivity) costs were calculated using retrospective Sydney Sexual Health Centre data. Costs included pathology, staff time, overheads, consumables, patient travel and forgone productivity. Statewide scale-up costs were estimated, with sensitivity analyses adjusting for inflation, minimum wage and an increase in the proportion of MyCheck users with productivity loss. RESULTS: From January to July 2023, Sydney Sexual Health Centre conducted 2548 screening episodes (45% MyCheck, 55% Xpress), with MyCheck attracting more men who have sex with men/transgender and gender diverse patients. MyCheck's shorter appointments (median 5 min vs Xpress's 15 min) led to lower staff costs (A$5 vs A$16). MyCheck had higher overall health system cost (A$127/patient) compared with Xpress (A$91/patient), mostly due to pathology costs. However, considering patient travel cost and productivity loss for Xpress, MyCheck's societal cost (A$137) was lower than Xpress (A$146), yielding A$104,260 annual savings. Statewide scale-up provides significant societal savings (A$419,077/year). CONCLUSION: This analysis of MyCheck's direct and indirect costs compared with traditional in-person screening demonstrates significant societal savings, despite higher direct pathology costs. It underscores the importance of a broader societal perspective in cost analyses. Lowering private pathology costs could further enhance MyCheck's cost-effectiveness. MyCheck, an innovative e-screening pathway, reduces barriers for STI/blood-borne virus screening by improving patient convenience and reduced opportunity costs. Despite higher direct pathology costs, its societal cost savings support statewide scale-up for improved screening accessibility.
9 Apr 2026
Read appraisal →Journal of clinical microbiology
Etiologies of community-acquired febrile illness identified by TaqMan Array Card qPCR on blood samples: a systematic review and meta-analysis
UNLABELLED: Community-acquired febrile illness presents a significant diagnostic challenge. The TaqMan Array Card (TAC) enables simultaneous detection of many bacterial, viral, parasitic, and fungal pathogens. This systematic review aimed to characterize the etiologies of community-acquired fever diagnosed by TAC directly on blood specimens. A systematic search of PubMed, Scopus, Embase, and Web of Science (from inception to January 2026 in English) identified studies using TAC to detect pathogens directly in human blood to identify the etiology of community-acquired febrile illness. Eligible studies were appraised using a modified Joanna Briggs Institute (JBI) checklist. Pooled proportions and meta-analyses were conducted using a random-effects model. A total of 16 studies comprising 8,937 participants from 12 African and Asian countries met inclusion criteria. TAC detected at least 1 pathogen in 0.43 (95% CI [0.32; 0.54]), with high between-study heterogeneity (I² = 99%). Parasitic infections were most common (56%), nearly all due to Plasmodium spp., followed by bacterial (26%), viral (22%), and fungal (0.5%) etiologies. Plasmodium spp., Rickettsia spp., dengue virus, Lassa fever virus, Streptococcus pneumoniae, Orientia tsutsugamushi, Mycobacterium tuberculosis complex, and Salmonella spp. were the most frequently identified pathogens. Culture-negative bacteria accounted for 56% of bacterial detections. Positivity with more than 1 organism occurred in 6% of cases. TAC showed strong concordance with blood culture for culturable organisms (positive agreement: 73%, 95%CI [0.53; 0.89]; negative: 98%, 95%CI [0.95; 1.00]). TAC provides culture-independent pathogen detection and reveals overlooked causes of febrile illness, such as culture-negative bacteria. Its application may improve clinical diagnosis and surveillance programs. IMPORTANCE: Accurate identification of the causes of community-acquired febrile illness is essential for guiding clinical decision-making, surveillance programs, and public health response. This systematic review and meta-analysis synthesizes data from more than 8,937 patients across Africa and Asia tested with blood-based TaqMan Array Card (TAC) assays. TAC enabled broad, culture-independent detection of bacterial, viral, parasitic, and fungal pathogens-revealing both expected causes, such as Plasmodium spp. and dengue virus, and neglected culture-negative bacteria including Orientia tsutsugamushi, Coxiella burnetii, and Rickettsia spp. By uncovering these underrecognized etiologies, TAC provides valuable pathogen-level data to strengthen fever surveillance, inform outbreak detection, and refine regional disease prioritization frameworks. These findings highlight the potential of high-throughput molecular diagnostics to enhance infectious disease control, particularly in resource-limited settings.
9 Apr 2026
Read appraisal →European journal of psychotraumatology
Emotion regulation skills training as an adjunctive treatment to narrative exposure therapy for posttraumatic stress disorder (PTSD) in refugees: a pilot randomized controlled trial
Background: Responses to evidence-based interventions for posttraumatic stress disorder (PTSD) in refugees vary considerably. Emotion regulation difficulties are associated with greater PTSD severity in refugees and thus represent a potential treatment target.Objective: This study aimed to test the efficacy of Skills Training in Affective and Interpersonal Regulation for Refugees (STAIR-R) and Narrative Exposure Therapy (NET) or Supportive Problem-Solving (SPS) and NET. An exploratory aim was to examine relative efficacy in refugees with high and low levels of visa and family insecurity.Methods: Seventy-one participants were randomly assigned to STAIR-R (6 sessions) + NET (7 sessions) or SPS (6 sessions) +NET (7 sessions). Assessments occurred at baseline, post-treatment, and 3-month follow-up, with additional self-report at mid-treatment. The primary outcome was clinician-assessed PTSD symptom severity (CAPS-5) and secondary outcomes included self-reported PTSD symptoms, depression symptoms, emotion regulation difficulties, difficulties in relationships and environmental quality of life.Results: Intent-to-treat linear mixed models showed no significant between-group differences at mid-treatment, post-treatment, or follow-up. Both groups demonstrated significant improvements at 3-month follow-up in clinician-assessed (STAIR-R + NET, g = -1.41; SPS + NET, g = -1.54, p < .001) and self-reported (STAIR-R + NET, g = -0.49; SPS + NET, g = -0.44, p = .006) PTSD symptoms. Moderatorg analyses revealed that those with high insecurity (n = 16) obtained greater benefits in STAIR-R + NET from pre-treatment to follow-up on self-reported PTSD (g = 1.35), depression (g = 1.11), emotion regulation difficulties (g = 1.24), relationship difficulties (g = 1.12) and quality of life (g = -1.05).Conclusions: While there were no overall between group-differences, refugees in both conditions showed reduced PTSD symptoms. There is preliminary evidence that those with high insecurity showed a better response to STAIR-R + NET than SPS + NET across several clinical outcomes, although the small sample size necessitates replication of these. These findings highlight the potential importance of tailored intervention approaches for refugees living in different environmental circumstances. Emotion regulation difficulties represent a promising treatment target for refugees with PTSD.A randomized controlled trial comparing Skills Training in Affective and Interpersonal Regulation for Refugees + Narrative Exposure Therapy (STAIR-R + NET) to Supportive Problem Solving Training + Narrative Exposure Therapy (SPS + NET) revealed no significant differences at 3-month follow-up, with both groups improving on PTSD symptoms.Moderator analyses provided preliminary evidence that refugees living with high insecurity (i.e. insecure visa or separated from all family) showed greater improvements following STAIR-R + NET than SPS + NET.
9 Apr 2026
Read appraisal →BMJ open
A double-blind, crossover, non-inferiority randomised controlled trial where primary care providers and patients compare human-generated and AI-generated digital health messages: the AI-CARE study protocol
INTRODUCTION: Primary care is facing multiple crises, including an increase in health misinformation. Digital health messaging by primary care providers has been shown to reach a diverse patient population. With the uptake of Generative Artificial Intelligence (GenAI) usage in healthcare, there is an important opportunity to rapidly create messages that are tailored to different populations and conditions. However, thoroughly assessing artificial intelligence (AI)-generated content is essential, as GenAI raises concerns regarding its accuracy, understandability, actionability and bias perpetuation. We aim to investigate whether digital health messages created by GenAI are evaluated as non-inferior compared with those created by human experts. METHODS AND ANALYSIS: The AI-CARE (AI to Create Accessible and Reliable patient Education materials) study is a double-blind, crossover, non-inferiority randomised controlled trial. Data collection began on 30 May 2025, and is expected to be completed at the end of May 2026. Over 12 months, 192 messages on 48 topics will be written: half by primary care and public health experts and half by a GenAI tool (OpenAI's ChatGPT). Review Panels composed of 24 primary care providers and 24 patients will evaluate these messages using an Evaluation Grid developed to assess the messages' quality of information, adaptation to the target audience, relevance and usefulness, and readiness to be shared with patients. Evaluations will be completed via online REDCap (Research Electronic Data Capture) surveys and the order in which the 192 messages appear will be randomised and will vary between individuals. Participants and analysts will be blinded to the generation source. The primary outcome will be the Clarity and Understandability score. ETHICS AND DISSEMINATION: The Research Ethics Boards of the Hôpital Montfort (24-25-11-038) and the University of Ottawa (S-12-24-11153) formally approved this study in December 2024. Reported data will be grouped and anonymised for dissemination in peer-reviewed scientific journals and conferences. TRIAL REGISTRATION NUMBER: NCT06997107.
9 Apr 2026
Read appraisal →BMJ open
Process evaluation of a basic life support educational intervention (FirstCPR cluster randomised study) delivered at community organisations in New South Wales, Australia.
BACKGROUND: The FirstCPR cluster randomised trial delivered multimodal basic life support (BLS) learning opportunities to community organisations. An a priori process evaluation examined intervention implementation, including participation, reach, uptake and member engagement. METHODS: The study used a multimethod process evaluation. Data were collected via semistructured interviews, focus group discussions, participant surveys, study records, web analytics and in-field observations. These sources captured participation patterns and implementation measures (delivery, reach, uptake and engagement: opt-in to digital messages and attendance at training sessions), as well as reasons for refusals and withdrawals. Qualitative data were analysed thematically and organised using the UK Medical Research Council process-evaluation framework. Qualitative and quantitative data were analysed separately and subsequently interpreted collectively to contextualise implementation patterns and identify barriers and enablers that influenced trial successes and failures. RESULTS: Intervention uptake and engagement varied significantly across organisations, with greater success observed in social and faith-based groups. Of the 82 intervention clusters, 78 (95%) received intervention materials; 74 (90%) engaged in at least one activity and 15 (18%) engaged in all activities. Participation was primarily driven by the organisation's leadership interest and support in providing BLS training to members, and by the time available to facilitate intervention activities. The presence of a dedicated liaison/champion emerged as the most critical enabler of member engagement and implementation. Feedback recommended concise, simple and culturally tailored modules, with practical components delivered in shorter, convenient sessions. Intervention delivery was affected by contextual challenges, including COVID-19 disruptions that limited in-field recruitment and group activities. CONCLUSIONS: Process evaluation can strengthen community-based interventions by identifying mechanisms and contextual factors that shape implementation and engagement. Partnering with social and faith-based organisations may be an effective approach to disseminating educational programmes such as life-saving skills to lay communities. Minimising research burden and ensuring organisational leadership support may improve participation while brief, practical and culturally tailored training may enhance engagement. TRIAL REGISTRATION NUMBER: ACTRN12621000367842.
9 Apr 2026
Read appraisal →BMJ open
Evaluation of equity in quality improvement for multiarterial grafting in females and patients with low socioeconomic status: retrospective analysis of a statewide collaborative database
OBJECTIVES: Quality collaboratives improve quality of care at the hospital and collaborative levels, but less is understood about how such efforts affect patient-level disparities. This study evaluated how a quality improvement (QI) effort (increasing multiarterial grafting during coronary artery bypass grafting (CABG)) translated into populations which historically receive lower-quality care (females and patients of low socioeconomic status). DESIGN: Retrospective cohort study. SETTING: All non-federal hospitals in the state of Michigan that perform cardiac surgery and participate in a statewide collaborative database (n=33). PARTICIPANTS: Patients undergoing first-time, isolated CABG receiving at least two bypass grafts from 2011 to 2022 were identified. PRIMARY ENDPOINTS: Association of sex and socioeconomic status with multiarterial grafting was evaluated across the study period. The distressed community index (DCI), a socioeconomic ranking (0-not distressed, 100-severely distressed), was matched to the patient's zip code. Hierarchical regression modelling was performed to associate DCI and sex with multiarterial grafting, incorporating patient factors and hospital and surgeon effects. A sex-surgery year and DCI-surgery year interaction term was performed to assess the change in the rate of multiarterial grafting. RESULTS: A total of 40 322 patients underwent CABG at 33 centres with a median age of 66 years and 24% were female. The rate of multiarterial grafting was 15%, although lower among females (10% vs 17%) and the highest (vs lowest) DCI quartile (14% vs 18%). After risk adjustment, females were less likely to receive multiarterial grafting (ORadj 0.51 (95% CI 0.45 to 0.58), p<0.001). Patients living in zip codes with a higher DCI had lower adjusted odds of receiving multiarterial grafting (ORadj 0.35 per 10-point increase (95% CI 0.24 to 0.51), p<0.001), a finding that was independent of study time (sex-year and DCI-year interaction terms p>0.05). CONCLUSIONS: Despite a large overall increase in multiarterial grafting due to QI efforts, females and patients with low socioeconomic status had lower rates of multiarterial grafting. QI efforts should be evaluated both overall and among patients who historically receive lower quality care to improve quality and equity.
9 Apr 2026
Read appraisal →Journal of medical Internet research
A Gamified Mobile Health Intervention to Promote Physical Activity, Executive Function, and Mental Health in College Students: Randomized Controlled Trial
BACKGROUND: College students commonly experience suboptimal health conditions, including insufficient physical activity (PA), excessive body weight, and declining physical fitness. Traditional interventions face low adherence, while gamified mobile health (mHealth) programs may improve engagement and outcomes. OBJECTIVE: This study aimed to evaluate the feasibility and effectiveness of a novel gamified, incentive-based mHealth intervention on primary outcomes (PA and adherence) and secondary outcomes (physical fitness, body composition, executive function [EF], and mental health). METHODS: A 2-arm parallel-group randomized controlled trial (RCT) was conducted in 2025 at Yantai University with 160 college students (18-25 years; BMI 18.5-30.0) who were randomized 1:1 (computer-generated, sex-stratified blocks of 4; concealed allocation) to the intervention group (IG) or control group (CG; n=80 each); major exclusions were contraindications to exercise, severe physical/mental illness, recent PA interventions, or psychotropic medication use. Both used the same fitness watch-app system and identical PA targets (≥150 min moderate-to-vigorous physical activity [MVPA] per week or ≥900 metabolic equivalent-minutes [MET-min] per week); IG additionally received team-based gamification (competition, points/leaderboards, feedback, and rewards), while CG received monitoring only. PA and adherence were monitored throughout the 8-week intervention; other outcomes were assessed at baseline and 8 weeks (fitness, body composition, EF, and mental health). Open-label with blinded outcome assessors/analysts; intention-to-treat (ITT) with multiple imputation. RESULTS: At 8 weeks, data were available for 154 participants (IG 78; CG 76); all 160 were analyzed per ITT. Compared to the CG, the IG demonstrated significantly higher mean levels in all primary PA outcomes over 8 weeks (daily steps: mean 10,356, SD 1245 versus 8242, SD 1087; Δ=2114; d=1.81, 95% CI 1.44-2.18; P<.001; daily MVPA: mean 71, SD 15 versus 43, SD 12 min; Δ=28 min; d=2.06, 95% CI 1.68-2.45; P<.001; and weekly MET-min: mean 1650, SD 310 versus 1340, SD 285; Δ=310; d=1.04, 95% CI 0.71-1.37; P<.001). Adherence was also higher in the IG (both P<.001). Key secondary outcomes, including skeletal muscle mass (Δ +0.54 kg), body fat percentage (Δ -0.46 percentage points), 800/1000 m run time (Δ -6.5 s), and depressive symptoms (Δ -2.0 points), significantly favored the IG (all P<.001). No serious adverse events occurred. CONCLUSIONS: This RCT demonstrated that integrating gamification into an mHealth platform significantly enhanced PA, intervention adherence, and selected health outcomes among college students. The key innovation lies in the trial design, which held the technology platform and activity goals constant across groups, thereby allowing a clearer estimate of the incremental contribution of gamification. Unlike many existing studies, this approach reduces confounding from co-occurring intervention components in between-group comparisons. It therefore provides more comparable and methodologically robust evidence on the specific efficacy of gamification in mHealth interventions. For real-world implementation, this model leverages the existing smartphone and wearable ecosystem, offering a low-cost, scalable strategy for university health-promotion programs.
8 Apr 2026
Read appraisal →JMIR human factors
Use of Digital Peer Support for Employee Well-Being: Retrospective Analysis Across Five Large Employers
BACKGROUND: Anonymous, 24/7 digital peer support (DPS) offers a scalable solution to support employees' emotional well-being. Understanding sociobehavioral factors, such as timing of engagement and the impact of shared resources, can help employers and employee assistance programs (EAPs) integrate digital tools to better support workforce well-being. OBJECTIVE: This study examines (1) outcomes via overall sentiment changes among DPS users; (2) sociobehavioral differences between employees who accessed real-time, anonymous DPS during versus outside business hours; (3) differences in sentiment outcomes based on time of use; and (4) the impact of in-session resource sharing on sentiment improvement. METHODS: Using OpenAI's large language model (LLM) GPT-4o-mini with a few-shot learning approach, 24,818 anonymous chat conversations from 13,879 employees at 5 large employers were evaluated for subclinical sentiment variables, including loneliness, sadness, stress, anxiety, depression, despair, helplessness, and optimism. RESULTS: Distinct activity patterns were observed between employees during and outside business hours, with a median user age of 36 years. During business hours, employees reported higher baseline stress (Δ1.6%), whereas outside business hours, baseline depression (Δ1.7%) and loneliness (Δ1.2%) were higher. After DPS use, LLM-derived negative sentiment scores decreased (loneliness 46% reduced, sadness 45%, stress 46%, anxiety ~39%, depression ~40%, despair ~40%, and helplessness ~38%), and optimism increased (~77%). Outside business hours, users engaged more (~68% of all sessions), remained in sessions 19% longer, and discussed 13% more topics, whereas users during business hours reported greater improvements in depression (Δ2.3%), helplessness (Δ1.9%), and loneliness (Δ0.5%). Resource sharing was associated with greater improvements in loneliness (Δ2.9%), stress (Δ1.3%), anxiety (Δ1.9%), depression (Δ7.3%), despair (Δ3.0%), helplessness (Δ2.8%), and optimism (Δ8.8%), but not sadness. CONCLUSIONS: DPS complements employers' EAPs by addressing employee engagement gaps, reducing barriers to mental health care, and promoting emotional well-being among the workforce.
8 Apr 2026
Read appraisal →Journal of medical Internet research
Social Media Intervention Based on the Information-Motivation-Behavioral Skills Model Promotes HIV Testing and Reduces High-Risk Behaviors Among Men Who Have Sex With Men in Resource-Limited Settings in China: Randomized Controlled Trial
BACKGROUND: Social media intervention may enhance HIV prevention among men who have sex with men, but the effect of this intervention in resource-limited settings remains unclear. OBJECTIVE: This randomized controlled trial evaluated whether a social media intervention grounded in the information-motivation-behavioral skills (IMB) model could be beneficial for HIV prevention among men who have sex with men in resource-limited settings. METHODS: Participants were recruited in Nanning, China, between April 2023 and April 2024. Eligible participants were randomly assigned to either the social media intervention group or the routine HIV prevention services control group. Participants in the intervention group received a 3-month social media intervention, which included completing video-based tasks. Baseline surveys were conducted, followed by follow-up surveys every 3 months, for a total of 2 follow-ups. Outcomes included HIV testing uptake, high-risk behavior, AIDS-related knowledge, safe sex self-efficacy, and attitude. RESULTS: A total of 180 eligible men who have sex with men were enrolled (90 per group). Follow-up rates were 97.8% (88/90) and 95.5% (86/90) for the intervention and control groups, respectively. At the follow-ups, the intervention group demonstrated significantly higher uptake of HIV testing, a lower proportion of participants reporting high-risk sexual behaviors, and higher condom use self-efficacy compared to the control group (all P<.05). After controlling for sociodemographic variables, generalized estimating equations analysis revealed that the intervention group had significantly higher odds of HIV testing (risk ratio [RR] 1.739, 95% CI 1.110-2.730), HIV self-testing (RR 2.306, 95% CI 1.593-3.340), and consistent condom use (RR 2.457, 95% CI 1.636-3.690) than the control group. Cochran-Armitage trend tests within the intervention group revealed that with increasing intervention duration, both HIV testing and HIV self-testing significantly increased, while high-risk sexual behaviors significantly decreased (all P<.05). CONCLUSIONS: The social media intervention guided by the IMB model demonstrated a positive effect on expanding HIV testing coverage, reducing high-risk behavior, enhancing AIDS-related knowledge, and improving safer sex self-efficacy among men who have sex with men in resource-limited settings. These findings provide valuable guidance for future HIV prevention and control efforts targeting this population.
8 Apr 2026
Read appraisal →Journal of the American Heart Association
Exposure to Volatile Organic Compounds and Cardiovascular Diseases: A Systematic Review and Meta-Analysis
BACKGROUND: Environmental pollution is an often-neglected contributor to cardiovascular disease (CVD). Volatile organic compounds (VOCs) are a subset of ubiquitous pollutants. Recent evidence has suggested exposure to VOCs as a possible contributor to CVD. We aimed to review the evidence for such a link between VOC exposure and cardiovascular outcomes. METHODS: PubMed, Web of Science, and Scopus were systematically searched for ecological and observational studies evaluating associations between exposure to VOCs and cardiovascular outcomes. The available evidence was synthesized qualitatively, and meta-analyses were conducted wherever multiple estimates were identified for a shared association. Sensitivity analyses were performed to evaluate the influence of individual studies on the pooled estimates. RESULTS: Thirty-six studies were included in the review. Pooled random-effects estimates for associations between VOC mixtures (odds ratio, 1.57 [95% CI, 0.79-3.11])/toluene, ethylbenzene, and xylene and CVD trended toward a positive effect while being imprecise. The pooled estimate for the association between exposure to benzene and CVD death also trended toward a positive effect (meta relative risk, 1.09 [95% CI, 0.99-1.21]; I2=91.4 [95% prediction interval, 0.82-1.46]). However, serious inconsistencies were noted on the significance and the magnitude of association. Fixed-effect analyses indicated significant positive effects in all evaluated associations. CONCLUSIONS: Evidence from studies evaluating ambient and individual VOC exposures suggests a possible association with increased CVD and CVD death. However, the heterogeneity noted between specific VOCs' effects, possible confounding, limited long-term exposure assessment, and sparse evaluation of mixture/copollutant effects warrant cautious interpretation of these findings and highlight the need for future high-quality prospective studies.
8 Apr 2026
Read appraisal →Environmental science & technology
Molecular Representation and Closed-Loop Validation for Toxicity Assessment of Organic Compounds in Ambient Air PM2.5
Although the health impacts of fine particulate matter (PM2.5) are primarily attributed to its chemically diverse composition rather than to mass concentration, assessing the toxicity of PM2.5 constituent compounds remains highly challenging due to chemical complexity and limited experimental scalability. This study introduces an interpretable machine learning (ML) framework using a curated A549 cytotoxicity data set (19,841 compounds) that integrates customized Molecular Access System (MACCS) fingerprints, six base models, and a stacking ensemble meta-model, all optimized with a biobjective strategy to assess the toxicity of organic compounds in PM2.5. The stacking ensemble model demonstrated satisfactory performance (test AUC > 0.8), exhibiting good generalization, adaptability, and robustness. Nontargeted analysis generated and experimentally validated a prediction set from the Hong Kong PM2.5 samples (51 of 387 compounds confirmed from 13 classes), demonstrating broad applicability on an independent Nanjing PM2.5 set (572 compounds). Key substructures driving toxicity, identified through a SHapley Additive exPlanations (SHAP) analysis and cell experimental validation, revealed that PM2.5 compounds with aromatic rings and nitrogen-based functional groups (e.g., aromatic α,β-unsaturated ketones, aromatic amines, aromatic nitro compounds, and tertiary amines) likely contribute to high toxicity. The derived "structure-toxicity" rules narrow the search space from thousands of compounds to those containing critical substructures, enabling efficient prioritization of toxic components and providing a foundation for improving model specificity and predictive accuracy in future studies.
8 Apr 2026
Read appraisal →BMJ open
Adverse childhood experiences and cognitive outcomes among older adults in low-income and middle-income countries: a systematic review
OBJECTIVES: While adverse childhood experiences (ACEs) have been consistently linked to poorer cognitive outcomes in later life, far less is known about ACEs' contribution to dementia and cognitive ageing risk in low-income and middle-income countries (LMICs), despite their growing and disproportionate share of global Alzheimer's disease and related dementias (ADRD) burden. This study aimed to systematically review existing evidence on the association between individual ACEs and cognitive outcomes among adults aged 40 years and older in LMIC settings. DESIGN: Systematic review and narrative synthesis. DATA SOURCE: We searched Medline, Embase, PsycINFO and CINAHL from the inception of each database to January 2026. ELIGIBILITY CRITERIA: Observational studies examining the association between individual ACEs and cognitive outcomes among adults aged 40 and older in LMICs. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened each record, assessed risk of bias using the Joanna Briggs Institute critical appraisal tool and extracted data. Results were illustrated using descriptive forest plots and a narrative synthesis. RESULTS: Our systematic review included 14 studies, primarily from upper-middle-income countries, that assessed the relationship between individual ACEs and cognitive impairment (n=4) and function (n=10). 10 studies reported significant associations between ACEs and poorer cognitive function and increased risk of cognitive impairment. No study assessed the association between ACEs and ADRD. Parental death, neglect and mental health issues in the family showed consistent associations with cognitive outcomes, whereas experiencing hunger and poor health in childhood showed inconsistent associations. CONCLUSIONS: Our review corroborated evidence from high-income countries that exposure to ACEs is associated with a long-term risk of poorer cognitive outcomes among older populations in LMICs. However, the available literature remains limited, with most studies originating from upper-middle-income countries, few examining cognitive impairment and none assessing ADRD. These findings underscore substantial gaps in knowledge and highlight the need for research across diverse LMIC settings to clarify the role of broader psychosocial and contextual childhood experiences in shaping cognitive ageing and dementia risk. PROSPERO REGISTRATION NUMBER: CRD42024501816.
8 Apr 2026
Read appraisal →JMIR human factors
Factors Influencing User Satisfaction in Accessing Health Data: Cross-Sectional Survey of United Kingdom Adults
BACKGROUND: While patient health records (PHRs) are becoming ubiquitous, nationwide evidence on the drivers of user satisfaction in the United Kingdom remains scarce. OBJECTIVE: This study aimed to quantify determinants of PHR user satisfaction in a nationally representative sample of United Kingdom adults and to contrast real-world experiences with hypothetical expectations among individuals without PHR exposure. METHODS: We conducted a cross-sectional online survey in March 2022 using stratified quota sampling (eg, age, sex, ethnicity) through the Prolific platform. Of 1001 respondents, 533 (53%) were female (mean age 41, SD13) years, 468 (47%) reported previous PHR use ("experienced" cohort), and 533 (53%) respondents did not ("hypothetical" cohort). Primary outcomes were five satisfaction items (5-point Likert), overall PHR evaluation (0-100), and stated/anticipated PHR functions. Two-sample t-tests with unequal variances examined between-group differences; multivariate analysis of variance (MANOVA) assessed demographic equivalence. Significance was set at P<.05. RESULTS: Respondents with PHR experience rated their record easy-to-use in 79% (370/468) of cases versus an anticipated 93% (498/533) among nonusers (P<.001). Experienced users rated appointment-scheduling time-saving at 68% (319/468) compared with 72% (387/533) of nonusers (P=.17). Mean overall evaluation scores were 71.0 (SD 19.5) versus 74.2 (SD 18.6) (t₉₉₇=2.25, P=.02). MANOVA confirmed demographic balance (Wilks Λ=.99, F₇,₉₉₃=1.48, P=.18). Preferred functions across cohorts were viewing personal health information (experience 81%, hypothetical 90%) and lab results (50% vs 76%). Users lacking experience consistently over-estimated future use of carer-related functions (eg, children's data: 36% vs 12%, P<.001). CONCLUSIONS: Adults in the United Kingdom value PHRs primarily for personal data access and scheduling convenience. Nonusers displayed optimistic expectations about carer-related features and breadth of functionality, indicating an information gap. Enhancing transparency about current capabilities and expanding features that facilitate caregiving could increase satisfaction and adoption.
7 Apr 2026
Read appraisal →JMIR dermatology
Community-Based Teledermatology for Urgent Suspected Skin Cancer: Health Economic Cost-Comparison and Discrete Event Simulation Study
BACKGROUND: The increasing incidence and financial burden of skin cancer place immense pressure on the UK's National Health Service (NHS). Systemic challenges, including dermatologist shortages and long waiting lists, complicate timely assessment of skin lesions for patients under the urgent suspected cancer pathway. While teledermatology offers an innovative solution compared to traditional face-to-face appointments, standard teledermatology models still face limitations in addressing health care access barriers. Community-based decentralized models may reduce such barriers, but the cost and operational impact of such specific models remain largely underresearched. OBJECTIVE: This study evaluated the differences in financial cost to the NHS and patient waiting times at the Northern Care Alliance NHS Foundation Trust by comparing a community-based teledermatology model using Pathpoint eDerma against the Trust's standard-of-care for patients in the urgent suspected skin cancer pathway. METHODS: This study used an ambidirectional design involving 2 distinct analyses. The cost comparison analysis (CCA) compared costs incurred under the teledermatology model (intervention arm, n=563) against the Trust's standard care, represented by a synthetic comparator arm (n=4011). The discrete event simulation (DES) modeled the operational impact on patient waiting times over a 1-year period. Data for the intervention arm were collected prospectively from December 2022 to May 2023 for CCA and up to November 2023 for DES, while comparator data were collected retrospectively from September 2021 to December 2022. Publicly available resource costs were incorporated to ensure the robustness of the analyses. RESULTS: The community-based teledermatology model was associated with significant improvements in both cost to the NHS and patient waiting times. The CCA revealed a mean cost saving of £45 (£1=US $1.24) per referral (95% CI £22-£60; P<.001). This cost saving was associated with a 26% reduction in the proportion of patients requiring a full diagnostic biopsy, falling from 48% (1925/4011) in standard care to 22% (124/563) in the teledermatology model as well as time savings in face-to-face clinics and administration. Furthermore, the DES demonstrated that, on average, the teledermatology pathways decreased the time to reach a clinical diagnosis by 9.90 (95% CI 9.64-10.16) days; to communicate a diagnosis to patients by 54.18 (95% CI 50.76-57.61) days; and to reach a histopathological diagnosis by 62.8 (95% CI 59.76-65.83) days compared to standard care. CONCLUSIONS: The implementation of the community-based teledermatology model appears to be a highly effective, cost-efficient strategy associated with shortened patient journeys. The intervention showed a faster initial triage phase, but the study identified the histopathology process as the next major systemic constraint that could deter further pathway efficiency. Achieving timely diagnosis for all patients, including those requiring diagnostic biopsies, will necessitate continued strategic investment in innovative technologies to accelerate this downstream process.
7 Apr 2026
Read appraisal →Prehospital and disaster medicine
Effectiveness of Video Call-Assisted Versus Voice Call-Assisted Dispatcher-Guided CPR in Untrained Laypersons: A Randomized Simulation Study
INTRODUCTION: Out-of-hospital cardiac arrest (OHCA) remains a major cause of mortality world-wide. Early bystander cardiopulmonary resuscitation (CPR) is a critical determinant of survival; however, many witnessed arrests are managed by untrained laypersons. Dispatcher-assisted CPR (DA-CPR) increases bystander intervention rates, but telephone-based guidance limits real-time assessment of compression quality. Video-assisted CPR (V-CPR) may overcome these limitations by enabling visual feedback and demonstration-based guidance. STUDY OBJECTIVE: The aim of this study was to evaluate whether video call-assisted dispatcher guidance incorporating simultaneous real-time demonstration improves CPR performance quality compared with voice call-assisted guidance in untrained laypersons during a simulated adult OHCA scenario. METHODS: This prospective, randomized, single-blind, manikin-based trial included 85 university students without prior CPR training. Participants were randomized to telephone-assisted CPR (T-CPR; n = 40) or video-assisted CPR (V-CPR; n = 45). All participants performed standardized hands-only CPR for five minutes following dispatcher instructions. In the V-CPR group, the dispatcher simultaneously demonstrated CPR on a manikin during the video call. The primary outcome was the composite CPR Quality Score generated by the manikin feedback system. Secondary exploratory outcomes included compression depth, compression rate, interruption time, and Emergency Medical Services (EMS)-related time intervals. Robust regression analysis adjusted for age, sex, dominant hand, height, and weight was performed. RESULTS: The mean age of participants was 20.13 (SD = 1.81) years, and 54.1% were female. The CPR Quality Score was significantly higher in the V-CPR group than in the T-CPR group (median difference -47; 95% CI, -60 to -36; P < .001). The V-CPR group demonstrated greater mean compression depth, higher proportions of compressions within recommended rate and depth ranges, and shorter interruption times between compressions. The T-CPR group showed shorter time from case recognition to EMS call, while the interval from dispatcher contact to CPR initiation was similar between groups. In multivariable robust regression analysis, allocation to the V-CPR group remained independently associated with higher CPR Quality Score and improved compression performance metrics. CONCLUSION: Video call-assisted dispatcher guidance incorporating simultaneous real-time visual demonstration significantly improves CPR quality in untrained lay rescuers compared with voice-only guidance. These findings suggest that structured visual modeling integrated into DA-CPR systems may enhance bystander resuscitation performance and help bridge gaps in community CPR training.
7 Apr 2026
Read appraisal →PloS one
Identifying minimal risk factors for adolescent suicidal ideation and suicide attempts: A machine learning-optimized approach.
This study aimed to develop and validate a machine learning (ML) model to identify the minimal risk factors for adolescent suicidal behaviors, including suicidal ideation and suicide attempts. Data from the Korea Youth Risk Behavior Web-based Survey (2022-2023), including 90,813 adolescents aged 12-18 years, were analyzed. Using multidimensional risk factors spanning sociodemographic, physical and mental health, and behavioral domains, we applied a Random Forest model combined with recursive feature elimination to identify a minimal subset of risk factors (optimal features). Model performance for identifying suicidal ideation and predicting suicide attempts was evaluated via area under the curve (AUC), sensitivity, specificity, and accuracy metrics across the validation datasets. Sadness, loneliness, anxiety, and stress were identified as optimal features, achieving a high AUC, sensitivity, specificity, and accuracy in identifying suicidal ideation and predicting suicide attempts. Additional factors further improved the ML model's predictive performance for suicide attempts, achieving an AUC of 97.28%, sensitivity of 93.49%, specificity of 90.21%, accuracy of 91.85%, a PPV of 90.52%, and an NPV of 93.26%. This study demonstrated the efficacy of ML-driven approaches in identifying critical risk factors for adolescent suicidal behaviors. The findings highlight the potential of ML frameworks to transform suicide prevention strategies and improve mental health outcomes in adolescents.
7 Apr 2026
Read appraisal →Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
A community based participatory research approach to evaluate barriers and facilitators for behavioral weight loss intervention implementation in a predominantly black community.
PURPOSE: Breast cancer survivors with overweight or obesity have worse breast cancer specific survival and outcomes as compared to those with average weight by Yung and Ligibel (Clin Adv Hematol Oncol 14:790-797, 2016) and Druesne-Pecollo et al. (Breast Cancer Res Treat 135:647-654, 2012). Our pilot Group-basEd Telehealth behavioral Weight Los (GET-WEL) Program showed that fewer Black breast cancer survivors (BBCS) enrolled and lost less weight than White breast cancer survivors by Allison et al. (Obesity Science and Practice 10:e70023, 2024). This study is aimed at using a community-based participatory research approach to assess barriers and facilitators of implementing a behavioral weight loss intervention among BBCS. METHODS: Eight BBCS from a predominantly Black community were invited to participate in semi-structured interviews that were voice recorded, transcribed, coded, and analyzed via comparative thematic analysis. RESULTS: Thematic analyses revealed multiple barriers within participants. These included lack of affordable healthy food access, safety concerns with regards to outdoor activities, lack of affordable fitness center memberships, time constraints related to competing work/life obligations, and steep learning curves with technology use. Most BBCS preferred an integrated community-based coach to guide their weight loss interventions via a combination of both virtual and in-person sessions. CONCLUSION: Our results indicate that a multimodal approach including nutrition education, reducing physical activity barriers, limiting time constraints by implementing both in-person and virtual platforms, and assisting with technology courses, is necessary to improve the equitable implementation of weight loss interventions. BBCS recommended utilizing established community facilities and leveraging known community members such as nutrition counselors and physical trainers to increase successful implementation.
6 Apr 2026
Read appraisal →Environmental geochemistry and health
Deciphering stone mining-induced hazardous heavy metal contamination in agricultural soils using source attribution, health-dietary risk analysis, and machine learning-driven insights
Mining activities significantly contribute to the release of hazardous heavy metals (HHMs) into agricultural soils, especially where stone extraction is intensive. This study assessed metal content, source identification, and possible health risks associated with HHMs (Cd, Pb, Cr, Cu, Ni) in stone mines affected agricultural soils of India. The results revealed that Zone 1 exhibited higher concentrations of Cr (308.95 ± 23.03 mg/kg), Ni (117.11 ± 16.21 mg/kg), and Cd (4.21 ± 1.26 mg/kg), surpasses the threshold limit set by WHO/FAO for agricultural soils. In contrast, Zone 2 had considerably lower HHMs concentrations for Cr (60.24 ± 10.68 mg/kg), Ni (31.61 ± 7.52 mg/kg) and Cd (0.66 ± 0.13 mg/kg). Geospatial distribution and self-organizing map (SOM) indicated spatial clustering of HHMs, with elevated concentrations centered in the southern part of the study area. Positive matrix factorization showed that geogenic sources and mining activities affect significantly to HHMs pollution. Monte Carlo simulation revealed that children are more prone to exposure to HHMs than adults, with ingestion identified as the primary exposure route. Hazard quotient values calculated from free ion activity model exceeded the threshold limit for Pb (1.59E+00) and Cd (6.32E-01). Severity adjustment margin of exposure highlighted severe human health risk for Cr and Ni. Random forest analysis indicated that bioavailable HHMs significantly influence the accumulation of metals in rice tissues which elevating dietary risk. The integration of robust statistical tools offers insights into the dynamics of HHMs contamination and provide policymakers and environmental scientists with useful information to mitigate the potential risks caused by mining on nearby agricultural lands.
5 Apr 2026
Read appraisal →Neurology
Long-Term Exposure to Ambient Air Pollution and Incident Amyotrophic Lateral Sclerosis: A Prospective Cohort Analysis of the UK Biobank
BACKGROUND AND OBJECTIVES: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with a complex etiology. Although a range of genetic and lifestyle factors have been implicated, the potential role of environmental airborne pollution exposure is uncertain. This study examined the association between long-term ambient exposure to air pollutants and the incidence of ALS in UK Biobank participants. METHODS: This prospective cohort study was based on the UK Biobank participants aged 40-69 years. The analytical sample comprised participants free of ALS at baseline and had complete data on air pollution exposure. Long-term exposure (2006-2021) to nitrogen dioxide (NO2), nitrogen oxides (NOX), fine particulate matter (PM2.5; <2.5 µm), and coarse particulate matter (PM10; <10 µm) was assessed using data from the UK Department for Environment, Food and Rural Affairs at a spatial resolution of 1 × 1 km. To evaluate the association between these pollutants and ALS risk, we used multivariable time-varying Cox proportional hazards models. Several sensitivity analyses were conducted to assess the robustness of the results. We also examined for gene-environment interaction stratified by C9orf72 status and UNC13A genotype. RESULTS: Among the 501,308 participants with a mean age of 56.5 (SD 8.1) years at baseline, 272,764 (54.4%) were female. Over a median follow-up of 8.4 years, 687 individuals developed ALS. We did not observe any associations for any of the examined pollutants and ALS risk. Specifically, the hazard ratios per SD increment for PM10, PM2.5, NOX, and NO2 were 1.03 (95% CI 0.92-1.15), 1.00 (95% CI 0.88-1.14), 1.01 (95% CI 0.90-1.13), and 1.00 (95% CI 0.89-1.12), respectively. Individuals living in areas with the highest tertile of air pollutant exposure, compared with those in the lowest tertile, did not show a higher risk of ALS across any of the pollutants examined (p for trend >0.05). Restricted cubic spline analyses revealed no nonlinear associations between air pollution and ALS risk (all p for nonlinearity >0.05). These results remained robust in various subgroup and sensitivity analyses. No evidence of gene-environment interaction was found. DISCUSSION: In this large population-based study with high statistical power, ambient air pollution was not a risk factor for the development of ALS.
5 Apr 2026
Read appraisal →Cancer causes & control : CCC
A preference study for applying mHealth to improve the quality of cervical cancer screening management from a supply and demand perspective: a discrete choice experiment.
OBJECTIVES: This study aims to investigate the preferences of women of cervical cancer screening age regarding the use of mobile health (mHealth) technologies in Xinjiang. The purpose is to enhance adherence and acceptance of mHealth applications, thereby improving the quality of cervical cancer screening follow-up for women residing in rural areas of Xinjiang. METHODS: The attributes and levels were established based on a comprehensive literature review and qualitative interviews. The choice set questionnaire was developed using SAS 9.4 through D-efficiency analysis. The research site was identified using a multi-stage sampling method, and the survey was launched in December 2024. An Optimal Logit model was selected for preference analysis, utilizing Stata 17.0. RESULTS: A total of six attributes were identified through the literature review and subsequently combined with qualitative interviews. The mixed logit regression results indicated that, among the six attributes, five were statistically significant (P < 0.05): mHealth approach, frequency of receiving notifications, reminder content, screening notification time, missionary form, and mission strategy. The results demonstrated a preference for WeChat as the mHealth approach (β = 0.230, P < 0.001, 95%CI 1.214-1.500), not accepting receiving notifications everyday (β = - 0.144, P = 0.001, 95%CI 0.797-0.940), preferred reminders containing positive information (β = 0.159,P = 0.001,95%CI1.068-1.288), opted for screening notifications 1 month in advance (β = 0.208, P < 0.001, 95%CI 1.133-1.339), and preferred the image form of education for missionary form (β = 0.118, P < 0.001, 95%CI 1.102-1.322). CONCLUSION: A one-size-fits-all approach should be avoided in the design of mHealth solutions to effectively address the diverse needs of individuals with varying preferences, thereby promoting the adoption of mHealth and improving the feasibility of its application.
5 Apr 2026
Read appraisal →PloS one
Caregivers' early stimulation behaviors on early child development outcomes in Northern Ghana
Despite the government prioritizing Early Childhood Development (ECD) in Ghana, data on responsive caregiving is limited. This study examined the type and extent of Early Stimulation Activities (ESAs) practiced by mothers, and other caregivers and the associations between ESAs and children's development by caregiver type in Northern Ghana. Data were from a cluster-randomized controlled trial with mother-child dyads that evaluated the impact of an integrated maternal mental health and early childhood intervention program. The primary outcome was measured by the Developmental Milestone Checklist (DMC-II). Covariates included maternal report of ESAs performed by herself, child's father, and other caregivers. Linear regression analyses with cluster-adjusted standard errors were performed. Nearly 15% of mother-participants (n = 313) reported 4 + ESAs in the past 3 days. Within the last 3 days, on average, women reported 2.5 activities for themselves, 1.2 activities by the child's father, and 2 activities by other caregivers. The associations between ESAs and children's development varied by caregiver type. Maternal stimulation was positively associated with children's total development and personal-social development, early stimulation by other caregivers was positively associated with children's total development and language development, and paternal stimulation was not associated with any development domain. Other associations included receipt of postnatal care and presence of household toys. While maternal stimulation seemed particularly important, findings regarding non-primary caregivers suggest that ECD programming could also benefit from their inclusion.
5 Apr 2026
Read appraisal →BMJ global health
Risk and protective factors of depression among caregivers of children with disabilities in rural Rwanda
BACKGROUND: Caregivers of children with disabilities are at increased risk of experiencing poor mental health due to the compound effects of financial and family stressors. This study aims to identify risk and protective factors for poor mental health, particularly depression, among caregivers of young children with disabilities. METHODS: This is a secondary data analysis, including a total of 1518 caregivers who were enrolled at baseline in a cluster randomised trial evaluating the effects of Sugira Muryango, a home-visiting parenting intervention, on early child development and violence prevention outcomes. A total of 309 primary caregivers were identified as having a child aged 12-36 months who screened positive for some form of developmental delay. Associations between key sociodemographic and household characteristics and depression outcomes were explored using multivariable linear regression models. RESULTS: Among the sample of caregivers of children with disabilities, 65% met the clinical cut-off for likely depression. Economic hardship (β=0.158, p<0.001), food insecurity (β=0.009, p<0.01) and caregiver illness (β=0.183, p<0.01) were significant risk factors for depression. In contrast, family unity (β=-0.013, p<0.001) was an important protective factor for depression among these caregivers. Among married/cohabiting caregivers, intimate partner violence (IPV) was associated with higher mean depression scores (β=0.306, p<0.001), though the inclusion of family unity in the full model (inclusive of risk and protective factors) attenuated the impact of IPV on depression. CONCLUSIONS: Programmes targeting children with disabilities should also address the mental health needs of parents. Mental health difficulties are common for caregivers living in poverty, especially those raising a child with a disability or developmental delay. Additionally, parenting programmes that reduce family violence and build family unity should be prioritised by policymakers interested in improving the mental health and well-being of families facing extreme poverty.
5 Apr 2026
Read appraisal →Vaccine
Applied immunoinformatics in modern vaccine design: a comprehensive review of available computational tools
The rapid evolution of computational biology has transformed vaccine design from a largely empirical process into a rational, data-driven discipline. At the center of this transformation lies immunoinformatics, which integrates immunology, molecular biology, and data science to accelerate the identification, evaluation, and optimization of vaccine candidates. By enabling the systematic transition from genomic data to viable immunotherapeutic candidates, these approaches offer an unprecedented capacity to shorten development timelines, reduce costs, and broaden population coverage compared to traditional trial-and-error vaccine pipelines. This review provides a state-of-the-art overview of the currently available immunoinformatic tool that underpins modern vaccine design. From identification of conserved and functionally essential pathogen targets, advances in structural prediction, epitope mapping, safety assessment, and systems-level analyses of host-pathogen interactions, immunoinformatics allows researchers to design vaccines with enhanced success rate. Special emphasis is placed on the shift from purely predictive models toward generative frameworks, where artificial intelligence and deep learning now support not only the evaluation, but also the rational engineering of optimized vaccine candidates. For this review, we systematically examined more than 250 computational tools and algorithms spanning every stage of the vaccine discovery pipeline. From this extensive survey, we distilled and discussed the approaches that currently demonstrate the highest performance and practical usability, thereby providing researchers with a curated overview of some the most reliable resources available.
5 Apr 2026
Read appraisal →Annals of medicine
An explainable online frailty prediction model for community-dwelling older adults based on machine learning algorithms: a cross-sectional study based on retrospective health data
BACKGROUND: Frailty is a significant health concern associated with diminished physiological reserves and increased healthcare burdens. Currently, effective models for predicting frailty risk are lacking. This study utilizes machine learning-based models to early identify community-dwelling older adults, enhancing risk assessment accuracy and guiding targeted interventions to slow frailty progression. METHODS: A cross-sectional analysis of data from 1,156 older adults across 31 community health centers in Nanjing, conducted between January and October 2024, was performed. Independent predictors of frailty were identified using univariate analysis and the least absolute shrinkage and selection operator. The dataset was divided into 70% training and 30% testing subsets. Six machine learning (ML) models were developed and their performances compared. The SHapley Additive exPlanations (SHAP) method was applied to interpret the models, and a web-based risk calculator was created. RESULTS: Our dataset showed that 22.3% of older adults were frail. Significant predictors of frailty were identified as age, education, medicine, vegetable, cognitive status, number of diseases, hemoglobin, total cholesterol, and neutrophil-to-lymphocyte ratio. Among the six ML models, Categorical Boosting (CatBoost) exhibited the highest performance, attaining an AUROC of 0.886 in the training set and 0.831 in the testing set. CONCLUSIONS: The developed CatBoost model and web calculator can be employed by general practitioners to proactively identify high-risk community-dwelling older adults, thereby enabling timely interventions to mitigate the progression of frailty. The tool's simplicity and replicability effectively facilitate the promotion and management of frailty prevention within the community. An effective model was developed to predict frailty risk in community-dwelling older adults.The integration of biomarkers and self-reported data enhances frailty prediction and optimizes risk-based intervention strategies.The CatBoost model demonstrates superior predictive performance compared to other models.The web-based tool integrates a frailty prediction model for proactive risk management.
5 Apr 2026
Read appraisal →Journal of behavioral addictions
When rejection backfires: Social exclusion and economic decision-making in gamblers
BACKGROUND AND AIMS: Economic decision-making deviates from rational choice models and is influenced by social factors, particularly fairness considerations and belonging needs. Social exclusion and altruistic punishment are intended to promote behavioral conformity, yet paradoxically may exacerbate rather than correct targeted behaviors among individuals with addictions already experiencing chronic rejection. Several preliminary studies show that social exclusion increases money desirability in general populations, however, the interaction between acute social exclusion and economic decision-making among individuals with gambling disorders (PGs)-marked by aberrant financial decision-making-remains unexplored. METHODS: In a field study, 203 gamblers were recruited outside gambling venues and randomized to experience either social inclusion or exclusion via Cyberball, a virtual ball-tossing paradigm. Participants then completed an ultimatum game, making accept/reject decisions on fair and unfair monetary offers, followed by the Problem Gambling Severity Index. RESULTS: Social exclusion increased unfair offer acceptance among PGs but had no effect on low- and moderate-risk gamblers. PGs accepted more unfair offers following exclusion than inclusion. Gambling severity had no effect on unfair offers acceptance. Neither social exclusion nor gambling severity affected fair offer acceptance. DISCUSSION AND CONCLUSIONS: Social exclusion triggered utilitarian decision-making only among PGs. This selective effect suggests rejection compromises PGs' economic decision-making processes, shifting priorities toward immediate monetary gains over equitable outcomes. These findings reveal how social punishment creates self-reinforcing cycles where exclusion triggers the utilitarian mindset characterizing problematic gambling. Treatment and societal approaches relying on social consequences may inadvertently strengthen harmful patterns, highlighting the need for inclusion-based interventions.
5 Apr 2026
Read appraisal →BMJ paediatrics open
Impact of parent education programmes on confidence and self-efficacy in parents of preterm infants: a systematic review
OBJECTIVE: Families of preterm infants can experience high stress during neonatal intensive care unit (NICU) hospitalisation, which interferes with the development of parenting confidence and self-efficacy through active engagement with their infants. Parent NICU support programmes provide guidance and education to build this connection. This systematic review examined the effects of parent education programmes on confidence and self-efficacy among parents of preterm infants. DESIGN: Systematic review in PubMed/Medline, PsycINFO, CINAHL, Google Scholar and Web of Science. SETTING: NICU. PARTICIPANTS: Parents of preterm infants. INTERVENTION: Education programmes offered to parents in the NICU. MAIN OUTCOME MEASURES: Quantitative surveys measuring parent confidence or self-efficacy. RESULTS: 14 studies met inclusion criteria from an initial 220 identified. Five were randomised controlled trials and nine were non-randomised studies. Programmes combining information delivery with opportunities for parent-infant engagement were most effective. Infant access and time to practise skills were key factors in transferring programme knowledge to increase parent confidence and self-efficacy. While 6 of the 14 studies did not show statistically significant differences between groups, all interventions demonstrated improvements in parental confidence or self-efficacy from baseline. Vast variability in duration of intervention, proper descriptions of facilitator trainings, methodological limitations and potential confounding factors reduced the overall quality of evidence to a low level. CONCLUSION: Both unit-specific programmes developed within individual NICUs and commercially available, copyrighted parent education programmes hold value. They are generally effective in building parent confidence and self-efficacy among parents of preterm infants. Integrating either type of programme into standard NICU care may hold promise for strengthening parental competence and promoting family-centred outcomes. Clarity on content/topics of programmes, duration and level of facilitator trainings can strengthen the process of supporting parents in the NICU, even in low resource settings. PROSPERO REGISTRATION NUMBER: CRD42024524063.
4 Apr 2026
Read appraisal →BMJ paediatrics open
Oxygen therapy for children with an oxygen saturation of 90-93% in Malawi: the NoGoLO2 pilot randomised controlled trial
OBJECTIVE: Oxygen is a cornerstone treatment for pneumonia with hypoxaemia. WHO guidelines recommend oxygen therapy for children with a peripheral arterial haemoglobin oxygen saturation (SpO2) <90%. Children in low- and middle-income countries with an SpO2 of 90-93% are at increased risk of mortality and may benefit from oxygen therapy. We aimed to determine the feasibility of a randomised controlled trial comparing standard of care (no oxygen), low-flow nasal cannula (LFNC) and high-flow nasal cannula (HFNC) among children with pneumonia and an SpO2 of 90-93%. DESIGN: Pilot, open-label, three-armed randomised control trial (NCT06176664). SETTING: Salima District Hospital, Malawi. PATIENTS: Children 1-59 months old with WHO-defined pneumonia and an SpO2 of 90-93%. INTERVENTIONS: Standard care (no oxygen), LFNC or HFNC. MAIN OUTCOME MEASURES: The primary outcome was feasibility defined as an average of ≤2 protocol deviations per participant. Secondary outcomes included consent refusal, participant attrition and treatment failure within 14 days. Treatment failure was defined as an SpO2 <90% for standard care participants or <94% in the LFNC and HFNC arms despite maximum therapy as described, any new severe respiratory distress (grunting, very severe chest indrawing) or any new WHO-defined emergency sign. RESULTS: Of the 29 eligible patients, 21 (72%) were enrolled and randomised. There was an average of 0.8 (16/21) deviations per participant. Seven (43.8%) protocol violations were related to study intervention protocols and nine (56.3%) to medication availability and routine care. No participants withdrew from the study. Three of 21 participants (14.3%) had treatment failure. All participants were successfully followed to obtain the 14-day outcome. CONCLUSIONS: A three-armed, open-label randomised control trial is feasible to compare standard of care, LFNC and HFNC oxygen for children with pneumonia and an SpO2 of 90-93% in Malawi. TRIAL REGISTRATION NUMBER: NCT06176664.
4 Apr 2026
Read appraisal →BMJ paediatrics open
Mapping the global prevalence and socioecological drivers of child sexual abuse: a systematic review and synthesis
INTRODUCTION: Child sexual abuse (CSA) is a widespread global health concern with lasting impacts. CSA is multifactorial and layered, and interventions to tackle CSA require an analysis of the key contributing factors. The main objective of this study was to explore global prevalence estimates of CSA and key contributing factors. METHODS: We systematically searched PubMed, Scopus and Web of Science for studies reporting lifetime prevalence of contact (eg, inappropriate touching or sexual acts) and non-contact (eg, exposure to sexual content or ill-intended conversations) CSA. Of 5493 articles screened, 332 met inclusion criteria. Prevalence data were stratified by population, region and abuse type. Risk factors were synthesised thematically using a socioecological framework. RESULTS: Median prevalence of reported non-contact CSA was 57.0% (range: 31.1%-80.0%). Contact CSA prevalence was higher among females (median: 14.9%, range: 2.2%-40.2%) than males (median: 6.0%, range: 0.6%-21.2%). Regional variations were notable, with sub-Saharan Africa reporting the highest contact CSA prevalence (median: 25.5%) and Latin America and the Caribbean the lowest (median: 8.5%). Vulnerable groups, including Indigenous children (median: 39.2%), orphans (37.9%) and the incarcerated (31.1%), faced higher risk. Risk factors spanned individual (shame, stigma), familial (poor supervision, dysfunction), institutional (lack of safeguards) and societal (weak legal frameworks, normalisation of abuse) levels. CONCLUSIONS: Prevalence of CSA was globally high, with 14 in 100 females reporting having experienced CSA. Multilevel interventions, particularly strengthening family supervision and institutional safeguarding, legal accountability and community awareness, are critical for the prevention of CSA.
4 Apr 2026
Read appraisal →JMIR aging
Digital Resources and Social Connectedness Among Ethnic Minority Older Adults: Systematic Review and Meta-Analysis
BACKGROUND: Being socially connected is essential for health and well-being. Nonetheless, many older adults face social isolation, especially in ethnically diverse societies. Digital technologies offer a pragmatic approach to addressing problems with social connectedness; however, a consolidated understanding of their association with social connectedness among ethnic minority older adults remains unaddressed. OBJECTIVE: We conducted a systematic review and meta-analysis to investigate the prevalence and utility of digital resources in promoting social connectedness among ethnic minority older adults. METHODS: This systematic review and meta-analysis was guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were retrieved from 4 electronic databases. A random-effects meta-analysis was used to estimate the pooled prevalence along with its 95% CI. RESULTS: Twelve studies were included. The research approaches used by the included studies were as follows: quantitative (n=5), qualitative (n=5), and mixed methods (n=2). Overall, the estimated prevalence of internet use, which was defined as engaging in online activities through digital devices, was 81.8%. Commonly used digital devices were computers (66.7%), smartphones (63.2%), and tablets (29.3%). Sociodemographic, economic, and health-related factors influenced the adoption and use of digital resources among ethnic minority older adults. These older adults relied on digital resources to build meaningful social connections through social participation, maintaining cultural and religious ties, promoting transnational social networks, and fostering their potential for social connectedness. However, digital resources were not always useful for social connectedness and adversely affected in-person contact. CONCLUSIONS: Digital resources can promote social connectedness among ethnic minority older adults by enabling them to maintain their cultural and social values. Cities and regions aiming to promote the social connectedness and well-being of ethnic minority older adults should consider intersectional factors that affect access to digital resources and the sustainable adoption of digital resources.
4 Apr 2026
Read appraisal →The Cochrane database of systematic reviews
Pharmacotherapy for mild hypertension
RATIONALE: This is an update of a Cochrane review published in 2012 of initiation of antihypertensive monotherapy or step-up therapy in people with untreated mild hypertension (systolic blood pressure 140 to 159 mmHg or diastolic blood pressure 90 to 99 mmHg, or both) and no pre-existing cardiovascular disease. The original review demonstrated no difference in the incidence of all-cause mortality, total cardiovascular events (stroke, myocardial infarction, and congestive heart failure), stroke incidence, coronary heart disease, or withdrawal due to adverse effects (WDAEs). Evidence for antihypertensive pharmacotherapy in people with mild hypertension for primary prevention remains uncertain in the literature with conflicting studies. We therefore performed an update of the original Cochrane review to reassess whether initiation of antihypertensive pharmacotherapy compared to placebo or no treatment in people with untreated mild hypertension and no pre-existing cardiovascular disease reduces the risk of all-cause mortality, total cardiovascular events, stroke, coronary heart disease, or WDAEs. OBJECTIVES: To reassess the efficacy and risks of initiating antihypertensive pharmacotherapy in adults with untreated mild hypertension and no pre-existing cardiovascular disease. The primary objective was to reassess the risk of all-cause mortality and total cardiovascular events (defined as fatal and non-fatal strokes, myocardial infarction, and congestive heart failure). The secondary objectives were to reassess the risk of stroke (fatal and non-fatal), coronary heart disease (fatal and non-fatal myocardial infarction and sudden cardiac death), and WDAEs. SEARCH METHODS: We searched the Cochrane Hypertension Specialised Register, CENTRAL, MEDLINE, Embase, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform from inception to June 2024. ELIGIBILITY CRITERIA: We included randomized controlled trials (RCTs) of at least one-year duration comparing initiation on antihypertensive monotherapy or step-up therapy, or both, versus placebo or no treatment in participants with mild hypertension and no pre-existing cardiovascular disease. OUTCOMES: Our critical outcomes were all-cause mortality and total cardiovascular events. Important outcomes were stroke, coronary heart disease (fatal and non-fatal myocardial infarction and sudden cardiac death), and WDAEs. RISK OF BIAS: Two review authors assessed risk of bias independently and in duplicate using Cochrane's RoB 1 tool. SYNTHESIS METHODS: Two review authors performed title and abstract screening, full-text review, and data extraction independently and in duplicate. We calculated risk ratio (RR) along with 95% confidence interval (CI) for all-cause mortality, total cardiovascular events, stroke events, coronary heart disease events, and WDAEs with the Mantel-Haenszel test and a fixed-effect model. We assessed the certainty of the evidence using the GRADE approach. INCLUDED STUDIES: We included individual patient data from five trials involving a total of 9124 participants, of whom 4593 received antihypertensives and 4531 received placebo or no treatment. All five trials reported all-cause mortality; four trials reported total cardiovascular events and strokes; three trials reported coronary heart disease; and one trial reported WDAEs. SYNTHESIS OF RESULTS: There may be little to no reduction in all-cause mortality (RR 0.85, 95% CI 0.64 to 1.14; 5 trials, 9124 participants; low-certainty evidence), total cardiovascular events (RR 0.93, 95% CI 0.69 to 1.24; 4 trials, 7292 participants; low-certainty evidence), or coronary heart disease (RR 1.12, 95% CI 0.80 to 1.57; 3 trials, 7080 participants; low-certainty evidence). There may be a decreased risk of stroke (RR 0.41, 95% CI 0.20 to 0.84; 4 trials, 7292 participants; low-certainty evidence) and an increase in WDAEs (RR 4.80, 95% CI 4.14 to 5.57; 1 trial, 17,354 participants [aggregate trial-level data; individual patient data unavailable]; low-certainty evidence) with antihypertensives. We downgraded the certainty of evidence for all outcomes due to imprecision, indirectness, and risk of bias. AUTHORS' CONCLUSIONS: In people with untreated mild hypertension and no pre-existing cardiovascular disease, initiation of antihypertensive monotherapy or step-up therapy may not reduce all-cause mortality, total cardiovascular events, or coronary heart disease compared to those who received placebo or no treatment. There may be a reduction in stroke, but possibly also an increase in WDAEs. FUNDING: CIHR Grant to the Hypertension Review Group and British Columbia Ministry of Health Grant to the Therapeutics Initiative. REGISTRATION: Protocol (2007): doi.org/10.1002/14651858.CD006742. Original review (2012): doi.org/10.1002/14651858.CD006742.pub2.
4 Apr 2026
Read appraisal →Journal of global health
Exposure-response association between outdoor activity time and myopia risk in Chinese children and adolescents: a systematic review and meta-analysis
BACKGROUND: The prevalence of myopia among Chinese children and adolescents has increased sharply over recent decades, raising concern about modifiable environmental risk factors. Although outdoor activity is widely recognised as protective, the quantitative exposure-response relationship within the Chinese educational context remains incompletely defined. METHODS: A systematic review and meta-analysis were conducted following PRISMA guidelines. Studies examining the association between daily outdoor activity time and myopia risk among Chinese youth were identified from major English and Chinese databases (Web of Science, PubMed, CNKI, and Wanfang) through October 2025. Random-effects meta-analysis was conducted to pool odds ratios (ORs). Prespecified subgroup and sensitivity analyses examined exposure thresholds, study design, and geographic latitude. RESULTS: We included 31 studies comprising 380 215 participants. Greater outdoor activity was consistently associated with lower myopia risk (pooled OR = 0.75; 95% confidence interval (CI) = 0.71-0.80), although substantial heterogeneity was observed (I2 = 94%). Compared with <1 hour per day, outdoor exposure of 1-2 hours (OR = 0.85; 95% CI = 0.79-0.92), 2-3 hours (OR = 0.86; 95% CI = 0.78-0.95), and > 3 hours (OR = 0.74; 95% CI = 0.63-0.87) was associated with reduced risk. When dichotomised at two hours, exposure >2 hours yielded an OR of 0.74 (95% CI = 0.69-0.80). Findings were directionally consistent across study designs and latitude strata. CONCLUSIONS: Greater outdoor activity time is associated with lower myopia risk among Chinese children and adolescents. An approximate daily exposure of around two hours appears to represent a pragmatic benchmark under current educational conditions.
4 Apr 2026
Read appraisal →BMJ global health
Impacts of rising food prices on nutritional outcomes and mortality of children in low and middle-income countries: a systematic review
BACKGROUND: Estimates indicate that 45% of mortality among children under 5-year old is linked to nutrition. Increased food prices can reduce access to nutritious foods, increasing nutritional and health risks for children, particularly in low and middle-income countries (LMICs). We synthesised evidence on the relationship of rising food costs with nutritional outcomes and mortality in children in LMICs. METHODS: EMBASE, MEDLINE, Global Health, EconLit, Web of Science and six grey literature sources were searched in September 2023. Searches included key phrases such as 'food price shocks' and 'child malnutrition'. We included any longitudinal study design, with any measure of food price increase and any measure of child malnutrition or mortality as outcomes. Results were analysed narratively with risk of bias assessed using the Newcastle Ottawa Scale. RESULTS: A total of 18 studies were included, covering 104 LMICs. There were 16 repeated cross-sectional or panel studies, one longitudinal cohort study and one quasi-experimental study. Five of these studies were multicountry. 16/18 studies reported a range of adverse nutritional outcomes associated with higher food costs, including mortality (five studies), stunting and low height for age (six studies), and wasting and low weight for height (five studies). Low birth weight, admissions to feeding centres, reduced consumption of rice, fruit, vegetables and animal protein, and reduced haemoglobin concentrations were also associated with higher food prices in one study each. Subgroup analyses were limited although two studies identified larger impacts on children in urban areas, and two studies identified larger impacts where children were exposed to higher food prices at younger ages. DISCUSSION: Rising food prices present a risk to child health and nutrition in LMICs. Policies should prioritise increasing household income alongside structural reforms to mitigate the nutritional impacts of elevated food prices on young children and pregnant women. PROSPERO REGISTRATION NUMBER: CRD42023469198.
4 Apr 2026
Read appraisal →Journal of behavioral addictions
Gambling in women: A systematic review of interventions and prevention approaches
BACKGROUND: Gambling disorder (GD) is a behavioral addiction with significant psychological, social, and economic consequences. Despite growing female participation and distinct gambling characteristics, research and interventions largely male-centered, overlooking women-specific factors. OBJECTIVES: This systematic review synthesizes evidence on prevention and treatment interventions for women with GD, assessing their effectiveness on gambling behaviors, cognitive and psychological outcomes, and identifying barriers related to access, adherence, and gender-sensitive design. METHOD: A systematic search in PubMed, PsycINFO, and Web of Science (up to September 2025) identified quantitative studies reporting female-specific outcomes in gambling prevention or treatment. Study quality was appraised using National Heart, Lung, and Blood Institute tools, and data on intervention characteristics, outcomes, and participant profiles were extracted. RESULTS: Eighteen studies met the inclusion criteria (five prevention, thirteen treatment). Prevention programs, mostly universal and adolescent-focused, improved gambling knowledge, cognitive distortions, and short term gambling frequency; however, socioemotional effects were inconsistent. Only one study included follow-up assessment. Treatment studies, predominantly cognitive behavioral therapy (CBT)-based, reduced gambling severity and psychological distress, although dropout and relapse rates were higher among women with greater psychopathology or limited support. Person-centered approaches benefited of tailoring interventions to individual profiles. No studies systematically applied gender-sensitive frameworks or disaggregated outcomes by sex in prevention. DISCUSSION AND CONCLUSION: Prevention and treatment programs can benefit women, but standard interventions insufficiently address their unique needs. Gender-sensitive, individualized strategies, inclusion of socioemotional factors, and long-term evaluations are essential to enhance outcomes and inform inclusive public health policies.
4 Apr 2026
Read appraisal →Journal of hazardous materials
Structuring large language models for chemical health risk reasoning in environmental and occupational exposure
Large language models (LLMs) have revolutionized numerous scientific fields. However, their application in environmental health remains limited, as they are prone to hallucinations and struggle with reasoning over complex, real-world exposure data. Chemical risks, especially from rare or poorly studied compounds, span diverse occupational and everyday scenarios, where structured knowledge is often incomplete and poorly integrated. To address these challenges, we present a health risk assistant that integrates deep learning-based compound property prediction, retrieval-augmented generation (RAG), and prompt engineering into a unified reasoning framework. Central to our design are two synergistic strategies: semantic structuring, which reorganizes heterogeneous knowledge into context-consistent and semantically rich profiles, and domain-aware prompting, which guides large language models through structured and role-specific reasoning aligned with toxicological goals. The framework enables the system to map physicochemical attributes to exposure pathways and disease outcomes with improved relevance and fidelity. Evaluated on a 100-question benchmark spanning chronic toxicity, occupational hazards, and exposure-specific risks, our LLM-RAG system consistently outperforms baseline models in correctness, faithfulness, and domain-specific helpfulness. Beyond answering queries, our approach demonstrates how integrated knowledge curation and tailored prompting can enable trustworthy and scalable AI reasoning for public and environmental health protection.
4 Apr 2026
Read appraisal →Journal of advanced research
Machine learning ensemble meets clinical practice: developing a real-world risk prediction model for metabolic syndrome using super learner and scorecard approaches
INTRODUCTION: Metabolic syndrome (MetS) refers to a cluster of metabolic abnormalities that significantly increase the risk of developing cardiovascular diseases (CVDs). Traditional binary definitions of MetS fall short in capturing its severity spectrum, limiting personalized risk stratification. OBJECTIVES: We aimed to develop a super learner model and multilevel risk scorecard to improve MetS risk prediction and support early cardiovascular risk identification. METHODS: This study included a total of 460,256 health examination records from Zhejiang, China (2018-2023), with 344,925 used for model development and 115,331 used for external validation. A super learner model combining multiple machine learning algorithms was constructed to predict MetS risk. Key predictors identified through feature selection were used to develop a logistic regression-based MetS risk scorecard, stratifying individuals into five risk levels for practical and interpretable applications. RESULTS: The super learner model achieved area under the receiver operating characteristics (AUCs) of 0.816 (95 % confidence interval [CI]: 0.814-0.817) and 0.810 (95 % CI: 0.808-0.813) in the development and external validation cohorts, respectively. The risk scorecard, which incorporates ten predictors, demonstrated comparable performance, with AUCs of 0.793 (95 % CI: 0.791-0.794) and 0.788 (95 % CI: 0.785-0.791) in the respective cohorts. Based on the risk scorecard, individuals were stratified into five categories: very low, low, normal, high, and very high risk levels. CONCLUSION: The super learner model provides a highly accurate tool for MetS risk prediction, whereas the risk scorecard offers a practical and interpretable solution for clinical and personal use. These models enable precise risk assessment to guide prevention and improve outcomes.
4 Apr 2026
Read appraisal →GeroScience
Integrative machine learning approach to risk prediction for dementia and Alzheimer's disease
Dementia, particularly Alzheimer's disease (AD), presents a growing global health challenge characterized by cognitive decline, behavioral changes, and loss of independence. With increasing life expectancy, early diagnosis and improved clinical strategies are urgently needed. This study developed and evaluated machine learning (ML) models to predict AD risk using UK Biobank data, integrating health, genetic, and lifestyle factors. The cohort included 2878 AD cases and 72,366 controls. Among several algorithms, CatBoost performed best (ROC-AUC = 0.773), especially in females. Inputs included ICD-10 codes from 5 years pre-diagnosis, ApoE-ε4 genotype, and large collection of modifiable risk factors. Despite fewer cases, the risk predictive models for vascular dementia (VaD) outperformed the unique AD models. ApoE-ε4 was the most predictive genetic marker, while other common variants had limited utility. Key non-genetic predictors included comorbidities (e.g., diabetes, hypertension), education, physical activity, and diet. These findings highlight the value of integrating diverse data sources for dementia risk prediction and emphasize the role of sex-specific modeling and modifiable factors in early, personalized intervention strategies.
2 Apr 2026
Read appraisal →BMC Palliat Care
Identification and mapping of mHealth interventions applied in palliative care in Sub Saharan Africa: a scoping review
BACKGROUND: Although palliative care is very essential for improving quality of life (QOL) by providing relief from pain and other distressing symptoms, its coverage in sub Saharan Africa remains remarkably low. Utilization of mHealth could be a fundamental healthcare system strengthening approach to enhance and promote palliative care in the region. There is paucity of evidence regarding evidence on the use of these interventions in SSA because it is a relatively new concept in the region. Therefore, there was need to identify and map the available/ applied mHealth interventions for palliative care in SSA basing on published and grey literature. AIM: To examine the nature and use of mHealth interventions for palliative care and factors influencing their use in sub Saharan Africa (SSA). METHODS: The review was based on the JBI methodology for scoping review. PUBMED, CINAHL, Embase and Google Scholar databases were searched for published articles with no time restrictions. Unpublished and grey literature was also searched for. Data was extracted from the retrieved sources and synthesized. The findings were reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) in a comprehensive and transparent way. RESULTS: A total of 224 articles were identified and 35 of these met the inclusion criterion and were considered for the review. The results show use of mHealth interventions for palliative care in 12 countries of the SSA. Only 12 (35.3%) were app-based, 9(26.5%) were SMS-text-based, 4(11.8%) were telemedicine-based,5(14.7%) were phone call-based, 3(8.8%) were mixed while 1(2.9%) used wearable-sensor-based mHealth interventions. Key uses of mHealth interventions in palliative care included health strengthening, psychosocial support to patients and families, enhancement of compliance to appointments for patients, promotion of adherence to medication, health education, monitoring, evaluation and research and capacity building for palliative care health professionals. A number of influencing factors were identified and they included wide-spread telephone ownership and access, great robustness of telephone and internet connectivity, high degree of perceived usefulness and ease of use, feasibility and acceptability of mHealth. Also, vital barriers such as low levels of technological advancement/expertise, irregularity and paucity of electric power supply, high likelihood to compromise patients' privacy and confidentiality and high illiteracy rates among the population were articulated by the articles. CONCLUSION: About a quarter of SSA countries have incorporated mHealth interventions for palliative care, underscoring the need for further research and development of the technologies. These approaches are quite beneficial to SSA, where there is a disproportionate disease burden and an inadequate healthcare system.
1 Feb 2026
Read appraisal →Clin Dermatol
Gonorrhea.
Neisseria gonorrhoeae, a Gram-negative intracellular pathogen, causes gonorrhea. Although usually sexually transmissible, it can be acquired by direct inoculation. Untreated gonococcal infections have deleterious impacts, including adverse pregnancy outcomes, ectopic pregnancy, infertility, and even blindness. Extended-spectrum cephalosporins remain the mainstay of therapy, and gonococcal culture is essential to determine susceptibility to these agents. Antimicrobial resistance is a global public health concern, and a few new agents are in the pipeline. Gonorrhea control programs rely on health education, access to diagnostic testing (where possible), effective therapy, and partner notification. Introducing inexpensive, sensitive, and specific point-of-care tests will aid antimicrobial stewardship efforts in countries using the syndromic management approach. Targeted vaccination of higher-risk populations with cross-protective outer membrane vesicle-based meningococcal B vaccines might reduce N. gonorrhoeae transmission in the future. Doxycycline postexposure prophylaxis may further reduce gonococcal incidence in the short term; however, its long-term impact on the human resistome/microbiome remains unknown.
1 Jan 2026
Read appraisal →JAMA
An AI-Powered Lifestyle Intervention vs Human Coaching in the Diabetes Prevention Program: A Randomized Clinical Trial
IMPORTANCE: Prediabetes is common, yet evidence-based lifestyle interventions are underutilized. OBJECTIVE: To determine whether referral to an exclusively artificial intelligence (AI)-led lifestyle intervention based on the Diabetes Prevention Program (DPP) is noninferior to referral to a human-led DPP in achieving recommended thresholds for weight loss, hemoglobin A1c (HbA1c) reduction, and weekly physical activity among adults with prediabetes and overweight or obesity. DESIGN, SETTING, AND PARTICIPANTS: This phase 3, parallel-group, pragmatic, noninferiority randomized clinical trial was conducted from October 11, 2021, to December 16, 2024 (last follow-up) at 2 US clinical sites in Baltimore, Maryland, and Reading, Pennsylvania. Adults 18 years or older with prediabetes and overweight or obesity were enrolled. INTERVENTIONS: Participants were randomized in a 1:1 ratio to receive either a referral to an AI-powered DPP lifestyle intervention delivered via a mobile app and Bluetooth-enabled digital scale or a referral to a human coach-led DPP lifestyle intervention delivered remotely. Both interventions were delivered independently of the study team over a 12-month period. MAIN OUTCOMES AND MEASURES: The primary outcome was a composite of maintaining an HbA1c less than 6.5% throughout the study and achievement of at least 5% weight loss, at least 4% weight loss plus at least 150 minutes of weekly physical activity (assessed with actigraphy), or an absolute reduction in HbA1c of at least 0.2 percentage points at 12 months. Noninferiority of referral to the AI-led DPP compared with referral to the human-led DPP was prespecified to be determined if the 1-sided 95% CI lower boundary of the risk difference did not cross -15%. RESULTS: A total of 368 participants were included (median [IQR] age, 58 [50-65] years; 71% were female, 27% were Black, 6% were Hispanic, and 61% were White; median [IQR] BMI, 32.3 [28.5-37.1]). After referral, 171 of 183 participants (93.4%) initiated the AI-led DPP and 153 of 185 (82.7%) initiated the human-led DPP. The primary outcome was achieved by 58 of 183 participants (31.7%) in the AI-led DPP group and 59 of 185 (31.9%) in the human-led DPP group (risk difference, -0.2% [1-sided 95% CI, -8.2%]), meeting the criterion for noninferiority. Findings were consistent across individual components of the composite end point and in sensitivity analyses. CONCLUSIONS AND RELEVANCE: Among adults with prediabetes and overweight or obesity, referral to a fully automated AI-led DPP was noninferior to referral to a human-led DPP in achieving a composite outcome based on weight reduction, physical activity, and HbA1c. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05056376.
1 Dec 2025
Read appraisal →Nat Hum Behav
Machine learning-assisted optimization of dietary intervention against dementia risk
A healthy diet has been associated with a reduced risk of dementia. Here we devised a Machine learning-assisted Optimizing Dietary intERvention against demeNtia risk (MODERN) diet based on data from 185,012 UK Biobank participants, 1,987 of whom developed all-cause dementia over 10 years. We first identified 25 food groups associated with dementia in a food-wide association analysis. Second, we ranked their importance using machine learning and prioritized eight groups (for example, green leafy vegetables, berries and citrus fruits). Finally, we established and externally validated a MODERN score (0-7), which showed stronger associations with lower risk of dementia-related outcomes (hazard ratio comparing highest versus lowest tertiles: 0.64, 95% CI: 0.43-0.93) than the a priori-defined MIND diet (0.75, 0.61-0.92). Across 63 health-related outcomes, the MODERN diet showed particularly significant associations with mental/behavioural disorders. Multimodal neuroimaging, metabolomics, inflammation and proteomics analyses revealed potential pathways and further support the potential of MODERN diet for dementia prevention.
1 Nov 2025
Read appraisal →Ann Allergy Asthma Immunol
Current updates in the epidemiology and comorbidities of atopic dermatitis
Atopic dermatitis (AD) is a chronic, inflammatory skin disorder that affects individuals across the lifespan, with significant implications for both public health and individual well-being. This paper provides an overview of the epidemiology of AD, focusing on its prevalence, incidence, and risk factors across different populations and regions. We evaluate the growing global burden of AD, highlighting trends in both high-income and low- to middle-income countries, and the impact of socioeconomic, environmental, and genetic factors on disease manifestation. The review also explores the variations in disease severity, age of onset, and comorbidities such as asthma and allergic rhinitis. This paper emphasizes the need for more robust epidemiologic studies to further elucidate the complex interactions between genetic predisposition and environmental exposures in the development and progression of AD and explores the potential role of technology (eg, artificial intelligence) in helping to collect robust epidemiologic data. Understanding the epidemiology of AD is crucial for identifying high-risk groups, informing preventive strategies, and optimizing management approaches.
1 Nov 2025
Read appraisal →J Pain Symptom Manage
First-Ever Global Ranking of Palliative Care: 2025 World Map Under the New WHO Framework
CONTEXT: Despite progress in policy and advocacy, global palliative care development remains highly uneven, with large segments of the population lacking access to quality services. A new WHO framework has provided an updated methodology for assessing national palliative care systems. OBJECTIVES: To assess the current state of palliative care development worldwide using the WHO framework and to produce the first global ranking of countries based on their performance across 14 indicators. METHODS: A cross-sectional, mixed-methods study was conducted across 201 countries and territories between 2023 and 2025. Trained national consultants conducted a structured survey based on WHO indicators. Scores were assigned across six domains: policy, essential medicines, service delivery, education, research, and community empowerment. Responses were validated and analyzed to produce a Global Development Score and to classify countries into four development levels: Emerging, Progressing, Established, and Advanced. RESULTS: Of the 201 countries assessed, 40% were classified as Emerging and 28% as Progressing, representing half the global population. Only 14% reached the Advanced level, and 17% were classified as Established. Significant gaps in access to essential medicines and specialized education persist-even in some high-income settings. Despite limited resources Thailand, Uganda,Chile, and Uruguay stand out as regional examples of advanced development. CONCLUSION: This study presents the first global ranking of palliative care development based on WHO indicators. The results highlight persistent disparities and offer a tool for targeted improvement. The Global Development Score enables countries to benchmark progress, identify gaps, and develop strategic responses to expand access and alleviate serious health-related suffering.
1 Nov 2025
Read appraisal →Acad Pediatr
Caregiver and Pediatric Clinician Perspectives on Artificial Intelligence for Language Services
OBJECTIVE: Children and caregivers who use languages other than English (LOE) for pediatric health care experience inequities and poorer overall health. Advancement of large language models has raised questions about the future use of artificial intelligence (AI) for language access. This study explored the perspectives of caregivers who use LOE and pediatric clinicians on using AI to address unmet needs in health care translation and interpretation. METHODS: We conducted semistructured individual interviews with caregivers of pediatric patients who use LOE and pediatric clinicians about the use of AI language technologies in health care. A phone interpreter or fluent team member was used for LOE interviews. Recordings were transcribed, translated as needed, coded, and analyzed using inductive thematic analysis. RESULTS: Twenty caregivers using 11 different LOE and 22 clinicians participated. Themes were consistent across participants, though clinicians were more familiar with the concept of AI. Participants reported use of technologies (eg, Google Translate) for written communication and situations where verbal interpretation was perceived to be inadequate. They were concerned about AI accuracy, privacy, and loss of empathy, but hoped it could provide real-time document translation and more convenient verbal communication. Ease of use, validation, and equitable creation and access were critical for use. CONCLUSIONS: Caregivers and clinicians were open to using AI to fill gaps in translation and interpretation; however, robust validation of AI technology and complementary use with human interpreters and translators is needed. Future research, practice, and policy should focus on integrating AI while investing in human translation and interpretation.
1 Jan 2025
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